Sequence Kernel Association Test Research Articles

Pharmacogenomics of intravenous immunoglobulin response in Kawasaki disease.

Kawasaki disease (KD) is a diffuse vasculitis in children. Response to high dose intravenous gamma globulin (IVIG), the primary treatment, varies according to genetic background. We sought to identify genetic loci, which associate with treatment response using whole genome sequencing (WGS). We performed WGS in 472 KD patients with 305 IVIG responders and 167 non-responders defined by AHA clinical criteria. We conducted logistic regression models to test additive genetic effect in the entire cohort and in four subgroups defined by ancestry information markers (Whites, African Americans, Asians, and Hispanics). We performed functional mapping and annotation using FUMA to examine genetic variants that are potentially involved IVIG non-response. Further, we conducted SNP-set [Sequence] Kernel Association Test (SKAT) for all rare and common variants. Of the 43,288,336 SNPs (23,660,970 in intergenic regions, 16,764,594 in introns and 556,814 in the exons) identified, the top ten hits associated with IVIG non-response were in FANK1, MAP2K3:KCNJ12, CA10, FRG1DP, CWH43 regions. When analyzed separately in ancestry-based racial subgroups, SNPs in several novel genes were associated. A total of 23 possible causal genes were pinpointed by positional and chromatin mapping. SKAT analysis demonstrated association in the entire MANIA2, EDN1, SFMBT2, and PPP2R5E genes and segments of CSMD2, LINC01317, HIVEPI, HSP90AB1, and TTLL11 genes. This WGS study identified multiple predominantly novel understudied genes associated with IVIG response. These data can serve to inform regarding pathogenesis of KD, as well as lay ground work for developing treatment response predictors.

TRANSETHNIC META-ANALYSIS OF INTERACTIONS BETWEEN GENETICS AND EARLY-LIFE SOCIOECONOMIC CONTEXT ON COGNITION

Abstract Later-life cognitive function is influenced by genetics as well as early- and later-life socioeconomic context. However, few studies have examined the interaction between genetics and early childhood factors. Using gene-based tests (interaction sequence kernel association test [iSKAT]/iSKAT optimal unified test), we examined whether common and rare variants in 39 gene regions previously associated with cognitive performance, dementia, and related traits had an interaction with childhood socioeconomic context (parental education and financial strain) on memory performance or decline in European ancestry (EA, N = 10,468) and African ancestry (AA, N = 2,252) participants from the Health and Retirement Study. Of the 39 genes, 22 in EA and 19 in AA had nominally significant interactions with at least one childhood socioeconomic measure on memory performance and/or decline; however, only one, SLC24A4 x father’s education, remained significant after multiple testing correction (false discovery rate [FDR] < .05). In trans-ethnic meta-analysis, 2 genes interacted with childhood socioeconomic context: MS4A4A x mother’s education on memory performance, and SLC24A4 x father’s education on memory decline. Both interactions remained significant after adjusting for respondent’s own education, apolipoprotein-ε4 allele status, lifestyle factors, body mass index, and comorbidities. For both interactions in EA and AA, the genetic effect was stronger in participants with low parental education. Examination of common and rare variants in genes discovered through genome-wide association studies shows that childhood context may interact with gene regions to jointly impact later-life memory function and decline. Genetic effects may be more salient for those with lower childhood socioeconomic status.

Identifying the joint signature of brain atrophy and gene variant scores in Alzheimer’s Disease

The joint modeling of genetic data and brain imaging information allows for determining the pathophysiological pathways of neurodegenerative diseases such as Alzheimer’s disease (AD). This task has typically been approached using mass-univariate methods that rely on a complete set of Single Nucleotide Polymorphisms (SNPs) to assess their association with selected image-derived phenotypes (IDPs). However, such methods are prone to multiple comparisons bias and, most importantly, fail to account for potential cross-feature interactions, resulting in insufficient detection of significant associations. Ways to overcome these limitations while reducing the number of traits aim at conveying genetic information at the gene level and capturing the integrated genetic effects of a set of genetic variants, rather than looking at each SNP individually. Their associations with brain IDPs are still largely unexplored in the current literature, though they can uncover new potential genetic determinants for brain modulations in the AD continuum. In this work, we explored an explainable multivariate model to analyze the genetic basis of the grey matter modulations, relying on the AD Neuroimaging Initiative (ADNI) phase 3 dataset. Cortical thicknesses and subcortical volumes derived from T1-weighted Magnetic Resonance were considered to describe the imaging phenotypes. At the same time the genetic counterpart was represented by gene variant scores extracted by the Sequence Kernel Association Test (SKAT) filtering model. Moreover, transcriptomic analysis was carried on to assess the expression of the resulting genes in the main brain structures as a form of validation. Results highlighted meaningful genotype–phenotype interactionsas defined by three latent components showing a significant difference in the projection scores between patients and controls. Among the significant associations, the model highlighted EPHX1 and BCAS1 gene variant scores involved in neurodegenerative and myelination processes, hence relevant for AD. In particular, the first was associated with decreased subcortical volumes and the second with decreasedtemporal lobe thickness. Noteworthy, BCAS1 is particularly expressed in the dentate gyrus. Overall, the proposed approach allowed capturing genotype–phenotype interactions in a restricted study cohort that was confirmed by transcriptomic analysis, offering insights into the underlying mechanisms of neurodegeneration in AD in line with previous findings and suggesting new potential disease biomarkers.

The burden of rare variants in DPYS gene is a novel predictor of the risk of developing severe fluoropyrimidine-related toxicity

BackgroundDespite a growing number of publications highlighting the potential impact on the therapy outcome, rare genetic variants (minor allele frequency < 1%) in genes associated to drug adsorption, distribution, metabolism, and elimination are poorly studied. Previously, rare germline DPYD missense variants were shown to identify a subset of fluoropyrimidine-treated patients at high risk for severe toxicity. Here, we investigate the impact of rare genetic variants in a panel of 54 other fluoropyrimidine-related genes on the risk of severe toxicity.MethodsThe coding sequence and untranslated regions of 54 genes related to fluoropyrimidine pharmacokinetics/pharmacodynamics were analyzed by next-generation sequencing in 120 patients developing grade 3–5 toxicity (NCI-CTC vs3.0) and 104 matched controls. Sequence Kernel Association Test (SKAT) analysis was used to select genes with a burden of genetic variants significantly associated with risk of severe toxicity. The statistical association of common and rare genetic variants in selected genes was further investigated. The functional impact of genetic variants was assessed using two different in silico prediction tools (Predict2SNP; ADME Prediction Framework).ResultsSKAT analysis highlighted DPYS and PPARD as genes with a genetic mutational burden significantly associated with risk of severe fluoropyrimidine-related toxicity (Bonferroni adjusted P = 0.024 and P = 0.039, respectively). Looking more closely at allele frequency, the burden of rare DPYS variants was significantly higher in patients with toxicity compared with controls (P = 0.047, Mann–Whitney test). Carrying at least one rare DPYS variant was associated with an approximately fourfold higher risk of severe cumulative (OR = 4.08, P = 0.030) and acute (OR = 4.21, P = 0.082) toxicity. The burden of PPARD rare genetic variants was not significantly related to toxicity. Some common variants with predictive value in DPYS and PPARD were also identified: DPYS rs143004875-T and PPARD rs2016520-T variants predicted an increased risk of severe cumulative (P = 0.002 and P = 0.001, respectively) and acute (P = 0.005 and P = 0.0001, respectively) toxicity.ConclusionThis work demonstrated that the rare mutational burden of DPYS, a gene strictly cooperating with DPYD in the catabolic pathway of fluoropyrimidines, is a promising pharmacogenetic marker for precision dosing of fluoropyrimidines. Additionally, some common genetic polymorphisms in DPYS and PPARD were identified as promising predictive markers that warrant further investigation.

A novel rare variants association test for binary traits in family-based designs via copulas.

With the cost-effectiveness technology in whole-genome sequencing, more sophisticated statistical methods for testing genetic association with both rare and common variants are being investigated to identify the genetic variation between individuals. Several methods which group variants, also called gene-based approaches, are developed. For instance, advanced extensions of the sequence kernel association test, which is a widely used variant-set test, have been proposed for unrelated samples and extended for family data. Family data have been shown to be powerful when analyzing rare variants. However, most of such methods capture familial relatedness using a random effect component within the generalized linear mixed model framework. Therefore, there is a need to develop unified and flexible methods to study the association between a set of genetic variants and a trait, especially for a binary outcome. Copulas are multivariate distribution functions with uniform margins on the interval and they provide suitable models to capture familial dependence structure. In this work, we propose a flexible family-based association test for both rare and common variants in the presence of binary traits. The method, termed novel rare variant association test (NRVAT), uses a marginal logistic model and a Gaussian Copula. The latter is employed to model the dependence between relatives. An analytic score-type test is derived. Through simulations, we show that our method can achieve greater power than existing approaches. The proposed model is applied to investigate the association between schizophrenia and bipolar disorder in a family-based cohort consisting of 17 extended families from Eastern Quebec.

Variations in gender identity and sexual orientation of university students

Abstract Background Previous studies have shown that a small percentage of people in the general population have atypical gender identity and/or sexual orientation. Aim This study aimed to explore variations in gender identity and sexual orientation in university students and determine genetic factors associated with these variations. Methods Deviations from complete gender congruence and exclusive heterosexual orientation in 736 Japanese university students were quantitatively assessed with self-assessment questionnaires. Next, we conducted genetic tests for 80 participants who showed relatively low gender identity scores and/or atypical sexual orientation. These genetic tests consisted of repeat number analysis of the androgen receptor gene (AR) and a SKAT-O: an optimal unified sequence kernel association test, which is an exome-based rare variant association study. The results of the genetic tests were compared with the Japanese reference data and the results of our 637 control samples. Outcomes We calculated the gender identity and sexual orientation scores of all participants and analyzed the molecular data of 80 selected participants. Results The gender identity scores of 736 participants were broadly distributed: only ~15% of natal males and ~5% of natal females had the maximum score that corresponds to complete gender congruence. The sexual orientation scores also varied: ~80% of natal males and ~60% of natal females showed exclusive heterosexual orientation. We found no association between gender characteristics and AR repeat numbers. The SKAT-O showed that rare damaging variants of TDRP and 3 other genes were more common in the 80 participants than in the control group. Clinical Implications Our data support the view that gender is a phenotypic continuum rather than a binary trait. Strength and Limitations This study quantitatively assessed the gender characteristics of a large cohort of university students. Moreover, we conducted systematic screening for genetic factors associated with gender variations. The weaknesses of the study were the limited analytic power of the questionnaires, the relatively small sample for molecular analyses, and incomplete clinical information and relatively advanced ages of the control group. Conclusion This study revealed significant variations in gender identity and sexual orientation in university students, which may be partly associated with variants in TDRP or other genes.

Whole Exome-Wide Association Identifies Rare Variants in GALNT9 Associated with Middle Eastern Papillary Thyroid Carcinoma Risk.

Papillary thyroid carcinoma (PTC) is the commonest thyroid cancer. The majority of inherited causes of PTC remain elusive. However, understanding the genetic underpinnings and origins remains a challenging endeavor. An exome-wide association study was performed to identify rare germline variants in coding regions associated with PTC risk in the Middle Eastern population. By analyzing exome-sequencing data from 249 PTC patients (cases) and 1395 individuals without any known cancer (controls), GALNT9 emerged as being strongly associated with rare inactivating variants (RIVs) (4/249 cases vs. 1/1395 controls, OR = 22.75, p = 5.09 × 10-5). Furthermore, three genes, TRIM40, ARHGAP23, and SOX4, were enriched for rare damaging variants (RDVs) at the exome-wide threshold (p < 2.5 × 10-6). An additional seven genes (VARS1, ZBED9, PRRC2A, VWA7, TRIM31, TRIM40, and COL8A2) were associated with a Middle Eastern PTC risk based on the sequence kernel association test (SKAT). This study underscores the potential of GALNT9 and other implicated genes in PTC predisposition, illuminating the need for large collaborations and innovative approaches to understand the genetic heterogeneity of PTC predisposition.

Rare sequence variants associated with the risk of non-syndromic biliary atresia.

The etiology of non-syndromic biliary atresia (BA) remains largely unknown. In this study, we performed genome-wide screening of genes associated with the risk of non-syndromic BA. We analyzed exome data of 15 Japanese patients with non-syndromic BA and 509 control individuals using an optimal sequence kernel association test (SKAT-O), a gene-based association study optimized for small-number subjects. Moreover, we examined the frequencies of known BA-related single nucleotide polymorphisms (SNPs) in the BA and control groups. SKAT-O showed that rare damaging variants of MFHAS1, a ubiquitously expressed gene encoding a toll-like receptor-associated protein, were more common in the BA group than in the control group (Bonferroni corrected p-value, 0.0097). Specifically, p.Val106Gly and p.Arg556Cys significantly accumulated in the patient group. These variants resided within functionally important domains. SKAT-O excluded the presence of other genes significantly associated with the disease risk. Of 60 known BA-associated SNPs, only eight were identified in the BA group. In particular, p.Ile3421Met of MYO15A and p.Ala421Thr of THOC2 were more common in the BA group than in the control group. However, the significance of these two variants is questionable, because MYO15A has been linked to deafness but not to BA and the p.Ala421Thr of THOC2 represents a relatively common SNP in Asia. The results of this study indicate that rare damaging variants in MFHAS1 may constitute a risk factor for non-syndromic BA, while the contribution of other monogenic variants to the disease predisposition is limited. This article is protected by copyright. All rights reserved.

An allelic-series rare-variant association test for candidate-gene discovery

Allelic series are of candidate therapeutic interest because of the existence of a dose-response relationship between the functionality of a gene and the degree or severity of a phenotype. We define an allelic series as a collection of variants in which increasingly deleterious mutations lead to increasingly large phenotypic effects, and we have developed a gene-based rare-variant association test specifically targeted to identifying genes containing allelic series. Building on the well-known burden test and sequence kernel association test (SKAT), we specify a variety of association models covering different genetic architectures and integrate these into a Coding-Variant Allelic-Series Test (COAST). Through extensive simulations, we confirm that COAST maintains the type I error and improves the power when the pattern of coding-variant effect sizes increases monotonically with mutational severity. We applied COAST to identify allelic-series genes for four circulating-lipid traits and five cell-count traits among 145,735 subjects with available whole-exome sequencing data from the UK Biobank. Compared with optimal SKAT (SKAT-O), COAST identified 29% more Bonferroni-significant associations with circulating-lipid traits, on average, and 82% more with cell-count traits. All of the gene-trait associations identified by COAST have corroborating evidence either from rare-variant associations in the full cohort (Genebass, n= 400,000) or from common-variant associations in the GWAS Catalog. In addition to detecting many gene-trait associations present in Genebass by using only a fraction (36.9%) of the sample, COAST detects associations, such as that between ANGPTL4 and triglycerides, that are absent from Genebass but that have clear common-variant support.

A pilot exome sequencing study suggests that germline variants influence methotrexate-induced toxicities in pediatric patients with localized osteosarcoma.

Osteosarcoma (OS) is a rare pediatric cancer for which therapeutic approaches, including chemotherapy and surgery, show a wide interindividual variability in patient response, both in terms of adverse events and therapy efficacy. There is growing evidence that this individual variable response to therapies is also influenced by inherited genetic variations. However, the results obtained to date in these pediatric cancers have been contradictory and often lack validation in independent series. Additionally, these studies frequently focused only on a limited number of polymorphisms in candidate genes. In order to identify germline coding variations associated with individual differences in adverse events occurrence in pediatric patients affected by localized OS, we carried out an exome-wide association study in 24 OS patients treated with methotrexate, cisplatin, and doxorubicin, using the SNP-Set (Sequence) Kernel Association Test (SKAT), optimized for small sample size. Gene sets significantly associated (FDR<.05) with neutropenia and hepatotoxicity induced by methotrexate were identified. Some of the identified genes map in loci previously associated with similar phenotypes (e.g., leukocyte count, alkaline phosphatase levels). Further studies in larger series and with functional characterization of the identified associations are needed; nonetheless, this pilot study prompts the relevance of broadly investigating variants along the whole genome, to identify new potential pharmacogenes, beyond drug metabolism, transport, and receptor candidate genes.

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance.

The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance. A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29-4.31, P=0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28-4.53, P=0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03-6.65, P=0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01-3.95, P=0.048; ORGRS 1.76; 95% CI: 1.16-2.69, P=0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09-5.68, P=0.03; HRGRS 2.44; 95% CI: 1.46-4.08, P<0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P=0.02). We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.

Genetic analysis of dystonia-related genes in Parkinson's disease.

Parkinson's disease (PD) and dystonia are two closely related movement disorders with overlaps in clinical phenotype. Variants in several dystonia-related genes were demonstrated to be associated with PD; however, genetic evidence for the involvement of dystonia-related genes in PD has not been fully studied. Here, we comprehensively investigated the association between rare variants in dystonia-related genes and PD in a large Chinese cohort. We comprehensively analyzed the rare variants of 47 known dystonia-related genes by mining the whole-exome sequencing (WES) and whole-genome sequencing (WGS) data from 3,959 PD patients and 2,931 healthy controls. We initially identified potentially pathogenic variants of dystonia-related genes in patients with PD based on different inheritance models. Sequence kernel association tests were conducted in the next step to detect the association between the burden of rare variants and the risk for PD. We found that five patients with PD carried potentially pathogenic biallelic variants in recessive dystonia-related genes including COL6A3 and TH. Additionally, we identified 180 deleterious variants in dominant dystonia-related genes based on computational pathogenicity predictions and four of which were considered as potentially pathogenic variants (p.W591X and p.G820S in ANO3, p.R678H in ADCY5, and p.R458Q in SLC2A1). A gene-based burden analysis revealed the increased burden of variant subgroups of TH, SQSTM1, THAP1, and ADCY5 in sporadic early-onset PD, whereas COL6A3 was associated with sporadic late-onset PD. However, none of them reached statistical significance after the Bonferroni correction. Our findings indicated that rare variants in several dystonia-related genes are suggestively associated with PD, and taken together, the role of COL6A3 and TH genes in PD is highlighted.

On asymptotic distributions of several test statistics for familial relatedness in linear mixed models.

In this study, the asymptotic distributions of the likelihood ratio test (LRT), the restricted likelihood ratio test (RLRT), the F and the sequence kernel association test (SKAT) statistics for testing an additive effect of the expected familial relatedness (FR) in a linear mixed model are examined based on an eigenvalue approach. First, the covariance structure for modeling the FR effect in a LMM is presented. Then, the multiplicity of eigenvalues for the log-likelihood and restricted log-likelihood is established under a replicate family setting and extended to a more general replicate family setting (GRFS) as well. After that, the asymptotic null distributions of LRT, RLRT, F and SKAT statistics under GRFS are derived. The asymptotic null distribution of SKAT for testing genetic rare variants is also constructed. In addition, a simple formula for sample size calculation is provided based on the restricted maximum likelihood estimate of the effect size for the expected FR. Finally, a power comparison of these test statistics on hypothesis test of the expected FR effect is made via simulation. The four test statistics are also applied to a data set from the UK Biobank.

Rare TMEM230 Variants are Potentially Associated With Early Onset Parkinson’s Disease (P3-11.013)

Rare TMEM230 Variants are Potentially Associated With Early Onset Parkinson’s Disease (P3-11.013)

The sequence kernel association test for multicategorical outcomes.

Disease heterogeneity is ubiquitous in biomedical and clinical studies. In genetic studies, researchers are increasingly interested in understanding the distinct genetic underpinning of subtypes of diseases. However, existing set-based analysis methods for genome-wide association studies are either inadequate or inefficient to handle such multicategorical outcomes. In this paper, we proposed a novel set-based association analysis method, sequence kernel association test (SKAT)-MC, the sequence kernel association test for multicategorical outcomes (nominal or ordinal), which jointly evaluates the relationship between a set of variants (common and rare) and disease subtypes. Through comprehensive simulation studies, we showed that SKAT-MC effectively preserves the nominal type I error rate while substantially increases the statistical power compared to existing methods under various scenarios. We applied SKAT-MC to the Polish breast cancer study (PBCS), and identified gene FGFR2 was significantly associated with estrogen receptor (ER)+ and ER- breast cancer subtypes. We also investigated educational attainment using UK Biobank data ( ) with SKAT-MC, and identified 21 significant genes in the genome. Consequently, SKAT-MC is a powerful and efficient analysis tool for genetic association studies with multicategorical outcomes. A freely distributed R package SKAT-MC can be accessed at https://github.com/Zhiwen-Owen-Jiang/SKATMC.

TRPA1 rare variants in chronic neuropathic and nociplastic pain patients.

Missing aspects of the heritability of chronic neuropathic pain, as a complex adult-onset trait, may be hidden within rare variants with low effect on disease risk, unlikely to be resolved by a single-variant approach. To identify new risk genes, we performed a next-generation sequencing of 107 pain genes and collapsed the rare variants through gene-wise aggregation analysis. The optimal unified sequence kernel association test was applied to 169 patients with painful neuropathy, 223 patients with nociplastic pain (82 diagnosed with chronic widespread pain and 141 with fibromyalgia), and 216 healthy controls. Frequency and features of variants in TRPA1, which was the most significant gene, were further validated in 2 independent cohorts of 140 patients with chronic pain (90 with painful neuropathy and 50 with chronic widespread pain) and 34 with painless neuropathy. The effect of aminoacidic changes were modeled in silico according to physicochemical characteristics. TRPA1 was significantly enriched of rare variants which significantly discriminated chronic pain patients from healthy controls after Bonferroni correction (P = 6.7 × 10-4, ρ = 1), giving a risk of 4.8-fold higher based on the simple burden test (P = 0.0015, OR = 4.8). Among the 32 patients harboring TRPA1 variants, 24 (75%) were diagnosed with nociplastic pain, either fibromyalgia (12; 37.5%) or chronic widespread pain (12; 37.5%), whereas 8 (25%) with painful neuropathy. Irrespective of the clinical diagnosis, 12 patients (38%) complained of itch and 10 (31.3%) of cold-induced or cold-accentuated pain, mostly episodic. Our study widens the spectrum of channelopathy-related chronic pain disorders and contributes to bridging the gap between phenotype and targeted therapies based on patients' molecular profile.

Children with Early-Onset Psychosis Have Increased Burden of Rare GRIN2A Variants.

Children and adolescents with early-onset psychosis (EOP) have more rare genetic variants than individuals with adult-onset forms of the illness, implying that fewer EOP participants are needed for genetic discovery. The Schizophrenia Exome Sequencing Meta-analysis (SCHEMA) study predicted that 10 genes with ultra-rare variation were linked to adult-onset schizophrenia. We hypothesized that rare variants predicted "High" and "Moderate" by the Variant Effect Predictor Algorithm (abbreviated as VEPHMI) in these 10 genes would be enriched in our EOP cohort. We compared rare VEPHMI variants in individuals with EOP (N = 34) with race- and sex-matched controls (N = 34) using the sequence kernel association test (SKAT). GRIN2A variants were significantly increased in the EOP cohort (p = 0.004), with seven individuals (20% of the EOP cohort) carrying a rare VEPHMI variant. The EOP cohort was then compared to three additional control cohorts. GRIN2A variants were significantly increased in the EOP cohort for two of the additional control sets (p = 0.02 and p = 0.02), and trending towards significance for the third (p = 0.06). Despite a small sample size, GRIN2A VEPHMI variant burden was increased in a cohort of individuals with EOP in comparison to controls. GRIN2A variants have been associated with a range of neuropsychiatric disorders including adult-onset psychotic spectrum disorder and childhood-onset schizophrenia. This study supports the role of GRIN2A in EOP and emphasizes its role in neuropsychiatric disorders.

NPC1 variants are not associated with Parkinson’s disease, REM-sleep behavior disorder or dementia with Lewy bodies in European cohorts

NPC1 encodes a lysosomal protein involved in cholesterol transport. Biallelic mutations in this gene may lead to Niemann-Pick disease type C (NPC), a lysosomal storage disorder. The role of NPC1 in alpha synucleinopathies is still unclear, as different genetic, clinical, and pathological studies have reported contradictory results. This study aimed to evaluate the association of NPC1 variants with the synucleinopathies Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and rapid eye movement–sleep behavior disorder (RBD). We analyzed common and rare variants from 3 cohorts of European descent: 1084 RBD cases and 2945 controls, 2852 PD cases and 1686 controls, and 2610 DLB cases and 1920 controls. Logistic regression models were used to assess common variants while optimal sequence Kernel association tests were used to assess rare variants, both adjusted for sex, age, and principal components. No variants were associated with any of the synucleinopathies, supporting that common and rare NPC1 variants do not play an important role in alpha synucleinopathies.

Evaluating the Genetic Role of Circadian Clock Genes in Parkinson's Disease.

Increasing evidence suggests that circadian dysfunction is related to Parkinson's disease (PD). However, the role of circadian clock genes in PD is still poorly understood. This study aimed to illustrate the association between genetic variants of circadian clock genes and PD in a large Chinese population cohort. Ten circadian clock genes were included in this study. Whole-exome sequencing (WES) was conducted in 1997 early-onset or familial PD patients and 1652 controls (WES cohort), and whole-genome sequencing (WGS) was conducted in 1962 sporadic late-onset PD patients and 1279 controls (WGS cohort). Analyses were completed using the optimized sequence kernel association test and regression analyses. In the burden analysis of the circadian clock gene set, we found suggestive significant associations between the circadian clock genes and PD in the WES cohort when considering missense, damaging missense (Dmis), and deleterious variants. Moreover, the burden analysis of single genes revealed suggestive significant associations between PD and the loss-of-function variants of the CRY1 gene, missense, Dmis, and deleterious variants of the PER1 gene, and Dmis and deleterious variants of the PER2 gene in the WES cohort.Rare variants in the WGS cohort and all common variants in the WGS and WES cohorts were unrelated to PD. Phenotypic analysis indicated that deleterious variants of the PER1 gene were associated with dyskinesia in the WES cohort. Our study provides evidence of a potential link between circadian clock genes and PD from a genetic perspective.

High-Depth PRNP Sequencing in Brains With Sporadic Creutzfeldt-Jakob Disease.

Sporadic Creutzfeldt-Jakob disease (sCJD) has established genetic risk factors, but, in contrast to genetic and acquired CJD, the initial trigger for misfolded prion aggregation and spread is not known. In this study, we tested the hypotheses that pathologic somatic variants in the prion gene PRNP are increased in sCJD, potentially leading to the seeding of misfolded prion protein. High-depth amplicon-based short read sequencing of the PRNP coding region was performed on postmortem brain tissue from patients with a clinical and neuropathologic diagnosis of sCJD (n = 142), Alzheimer disease (AD) (n = 51) and controls with no clinical or neuropathologic diagnosis of a neurodegenerative disease (n = 71). Each DNA sample was sequenced twice, including independent PCR amplification, library preparation, and sequencing. We used RePlow to call somatic variants with high sensitivity and specificity and optimal sequence kernel association test to compare variant burden between groups. Two sCJD cases had somatic (variant allele frequency 0.5-1%) PRNP variants not previously identified, but with high in silico predicated pathogenicity. However, the pathogenicity of these variants is uncertain, as both located in the octapeptide repeat region where no point variations have previously been associated with sCJD. There was no overall difference in burden somatic PRNP in sCJD compared with controls and a lower burden compared with Alzheimer disease. Somatic variants in PRNP are unlikely to play a major role in sCJD but may contribute to the disease mechanism in a minority of cases.