Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies

Insights into the genetic architecture of haematological traits from deep phenotyping and whole-genome sequencing for two Mediterranean isolated populations

Haematological traits are linked to cardiovascular, metabolic, infectious and immune disorders, as well as cancer. Here, we examine the role of genetic variation in shaping haematological traits in two isolated Mediterranean populations. Using whole-genome sequencing data at 22× depth for 1457 individuals from Crete (MANOLIS) and 1617 from the Pomak villages in Greece, we carry out a genome-wide association scan for haematological traits using linear mixed models. We discover novel associations (p < 5 × 10^–9) of five rare non-coding variants with alleles conferring effects of 1.44–2.63 units of standard deviation on red and white blood cell count, platelet and red cell distribution width. Moreover, 10.0% of individuals in the Pomak population and 6.8% in MANOLIS carry a pathogenic mutation in the Haemoglobin Subunit Beta (HBB) gene. The mutational spectrum is highly diverse (10 different mutations). The most frequent mutation in MANOLIS is the common Mediterranean variant IVS-I-110 (G>A) (rs35004220). In the Pomak population, c.364C>A (“HbO-Arab”, rs33946267) is most frequent (4.4% allele frequency). We demonstrate effects on haematological and other traits, including bilirubin, cholesterol, and, in MANOLIS, height and gestation age. We find less severe effects on red blood cell traits for HbS, HbO, and IVS-I-6 (T>C) compared to other b+ mutations. Overall, we uncover allelic diversity of HBB in Greek isolated populations and find an important role for additional rare variants outside of HBB.

Novel biomarkers for acute respiratory distress syndrome: genetics, epigenetics and transcriptomics

Acute respiratory distress syndrome (ARDS) can be induced by multiple clinical factors, including sepsis, acute pancreatitis, trauma, intestinal ischemia/reperfusion and burns. However, these factors alone may poorly explain the risk and outcomes of ARDS. Emerging evidence suggests that genomic-based or transcriptomic-based biomarkers may hold the promise to establish predictive or prognostic stratification methods for ARDS, and also to help in developing novel therapeutic targets for ARDS. Notably, genetic/epigenetic variations correlated with susceptibility and prognosis of ARDS and circulating microRNAs have emerged as potential biomarkers for diagnosis or prognosis of ARDS. Although limited by sample size, ethnicity and phenotypic heterogeneity, ongoing genetic/transcriptomic research contributes to the characterization of novel biomarkers and ultimately helps to develop innovative therapeutics for ARDS patients.

Thrombotic risk determined by protein C receptor (PROCR) variants among middle-aged and older adults: a population-based cohort study

BACKGROUND

The protein C (PC) anticoagulant system has a key role in maintaining hemostatic balance. One missense (Ser219Gly) variant in the protein C receptor (PROCR) was associated with venous thromboembolism (VTE) in genome-wide association studies.

OBJECTIVES

This study aimed to determine the thrombotic risk of rare and common PROCR variants in a large population-based cohort of middle-aged and older adults.

PATIENTS/METHODS

The exonic sequence of PROCR was analyzed for the Ser219Gly variant and other qualifying variants in 28,794 subjects (born 1923-1950, 60% women) without previous VTE, who participated in the Malmö Diet and Cancer study (1991-1996). Incidence of VTE was followed up until 2018. Qualifying variants were defined as loss-of-function or non-benign (PolyPhen-2) missense variants with minor allele frequencies (MAF) < 0.1%.

RESULTS

Resequencing identified 36 PROCR variants in the study population (26,210 non-VTE exomes and 2584 VTE exomes), 11 synonymous, 22 missense and three loss-of-function variants. Kaplan-Meier analysis of the known Ser219Gly variant (rs867186) showed that homozygosity for this variant increased the risk of disease whereas heterozygosity showed no effect. Cox multivariate regression analysis revealed an adjusted hazard ratio of 1.5 (95%CI 1.1-2.0). Fifteen rare variants were classified as qualifying and were included in collapsing analysis (burden test and SKAT-O). They did not contribute to risk. However, a Arg113Cys missense variant (rs146420040; MAF=0.004) showed an increased VTE risk (HR=1.3; 95%CI 1.0-1.9).

CONCLUSIONS

Homozygosity for the Ser219Gly variant and a previously identified functional PROCR variant (Arg113Cys) was associated with VTE. Other variants did not contribute to VTE.

Rare variant association tests for ancestry-matched case-control data based on conditional logistic regression

With the increasing volume of human sequencing data available, analysis incorporating external controls becomes a popular and cost-effective approach to boost statistical power in disease association studies. To prevent spurious association due to population stratification, it is important to match the ancestry backgrounds of cases and controls. However, rare variant association tests based on a standard logistic regression model are conservative when all ancestry-matched strata have the same case-control ratio and might become anti-conservative when case-control ratio varies across strata. Under the conditional logistic regression (CLR) model, we propose a weighted burden test (CLR-Burden), a variance component test (CLR-SKAT) and a hybrid test (CLR-MiST). We show that the CLR model coupled with ancestry matching is a general approach to control for population stratification, regardless of the spatial distribution of disease risks. Through extensive simulation studies, we demonstrate that the CLR-based tests robustly control type 1 errors under different matching schemes and are more powerful than the standard Burden, SKAT and MiST tests. Furthermore, because CLR-based tests allow for different case-control ratios across strata, a full-matching scheme can be employed to efficiently utilize all available cases and controls to accelerate the discovery of disease associated genes.

Identification of Potential Biological Factors Affecting the Treatment of Ticagrelor After Percutaneous Coronary Intervention in the Chinese Population

Background

Generally, many individual factors can affect the clinical application of drugs, of which genetic factors contribute more than 20%. Ticagrelor is a new class of receptor inhibitors receptor antagonist of P2Y12 and is used as an antiplatelet agents. But it is not affected by the influence of CYP2C19 polymorphism. With lack of predicted biomarkers, especially the research data of Chinese, it has the important significance in studying individual differences of ticagrelor in the antiplatelet efficacy and safety, through pharmacogenomics research.

Methods

Whole-exome sequencing (WES) was performed in 100 patients after PCI with ticagrelor treatment. Clinical characteristics and WES of patients were used to performed genome-wide association analysis (GWAS), region-based tests of rare DNA variant to find the influencing factors of antiplatelet effect to ticagrelor and bleeding events. Co-expression, protein–protein interaction (PPI) network and pathway enrichment analysis were then used to find possible genetic mechanisms. Atlas of GWAS (https://atlas.ctglab.nl/) were used for external data validation.

Results

DNAH17, PGS1 and ABCA1 as the potential variant genes are associated with the expected antiplatelet effect to ticagrelor. The affected pathways may include the synthesis and metabolism of lipoprotein cholesterol and the catabolic process of pyrimidine-containing compound (GO:0072529). Age, sex and PLT were found may be potential factors for ticagrelor bleeding events.

Conclusion

We systematically identified new genetic variants and some risk factors for reduced efficacy of ticagrelor and highlighted related genes that may be involved in antiplatelet effects and bleeding event of ticagrelor. Our results enhance the understanding of the absorption and metabolic mechanisms that influence antiplatelet response to ticagrelor treatment.

Trial Registration

ClinicalTrials.gov Identifier: NCT03161002. First Posted: May 19, 2017. https://clinicaltrials.gov/ct2/show/study/NCT03161002.

Rare variant association study of veteran twin whole-genomes links severe depression with a nonsynonymous change in the neuronal gene BHLHE22

OBJECTIVES

Major Depressive Disorder (MDD) is a complex neuropsychiatric disease with known genetic associations, but without known links to rare variation in the human genome. Here we aim to identify rare genetic variants associated with MDD using deep whole-genome sequencing data in an independent population.

METHODS

We report the sequencing of 1,688 whole genomes in a large sample of male-male Veteran twins. Depression status was classified based on a structured diagnostic interview according to DSM-III-R diagnostic criteria. Searching only rare variants in genomic regions from recent GWAS on MDD, we used the optimised sequence kernel association test and Fisher's Exact test to fine map loci associated with severe depression.

RESULTS

Our analysis identified one gene associated with severe depression, basic helix loop helix e22 (P_Adjusted = 0.03) via SKAT-O test between unrelated severely depressed cases compared to unrelated non-depressed controls. The same gene BHLHE22 had a non-silent variant rs13279074 (P_Adjusted = 0.032) based on a single variant Fisher's Exact test between unrelated severely depressed cases compared to unrelated non-depressed controls.

CONCLUSION

The gene BHLHE22 shows compelling genetic evidence of directly impacting the severe depression phenotype. Together these results advance understanding of the genetic contribution to major depressive disorder in a new cohort and link a rare variant to severe forms of the disorder.

Mutations in GBA, SNCA, and VPS35 are not associated with Alzheimer's disease in a Chinese population: a case-control study

SNCA, GBA, and VPS35 are three common genes associated with Parkinson’s disease. Previous studies have shown that these three genes may be associated with Alzheimer’s disease (AD). However, it is unclear whether these genes increase the risk of AD in Chinese populations. In this study, we used a targeted gene sequencing panel to screen all the exon regions and the nearby sequences of GBA, SNCA, and VPS35 in a cohort including 721 AD patients and 365 healthy controls from China. The results revealed that neither common variants nor rare variants of these three genes were associated with AD in a Chinese population. These findings suggest that the mutations in GBA, SNCA, and VPS35 are not likely to play an important role in the genetic susceptibility to AD in Chinese populations. The study was approved by the Ethics Committee of Xiangya Hospital, Central South University, China on March 9, 2016 (approval No. 201603198).

Analysis of rare coding variants in 200,000 exome-sequenced subjects reveals novel genetic risk factors for type 2 diabetes

AIMS

The study aimed to elucidate the effects of rare genetic variants on the risk of type 2 diabetes (T2D).

MATERIALS AND METHODS

Weighted burden analysis of rare variants was applied to a sample of 200,000 exome-sequenced participants in the UK Biobank project, of whom over 13,000 were identified as having T2D. Variant weights were allocated based on allele frequency and predicted effect, as informed by a previous analysis of hyperlipidaemia.

RESULTS

There was an exome-wide significant increased burden of rare, functional variants in three genes, GCK, HNF4A and GIGYF1. GIGYF1 has not previously been identified as a diabetes risk gene and its product appears to be involved in the modification of insulin signalling. A number of other genes did not attain exome-wide significance but were highly ranked and potentially of interest, including ALAD, PPARG, GYG1 and GHRL. Loss of function (LOF) variants were associated with T2D in GCK and GIGYF1 whereas nonsynonymous variants annotated as probably damaging were associated in GCK and HNF4A. Overall, fewer than 1% of T2D cases carried one of these variants. In HNF1A and HNF1B there was an excess of LOF variants among cases but the small numbers of these fell short of statistical significance.

CONCLUSIONS

Rare genetic variants make an identifiable contribution to T2D in a small number of cases but these may provide valuable insights into disease mechanisms. As larger samples become available it is likely that additional genetic factors will be identified.

Deciphering Genetic Susceptibility to Tuberculous Meningitis

Tuberculous meningitis (TBM) is the most severe form of extrapulmonary tuberculosis (TB) that arises when a caseating meningeal granuloma discharges its contents into the subarachnoid space. It accounts for ~1% of all disease caused by Mycobacterium tuberculosis and the age of peak incidence is from 2-4 years. The exact pathogenesis of TBM is still not fully understood and the mechanism(s) by which the bacilli initially invade the blood-brain-barrier are still to be elucidated. This study investigated the involvement of the host genome in TBM susceptibility, by considering common variants (minor allele frequency (MAF) >5%) using microarray genotyping and rare variants (MAF <1%) via exome sequencing. A total of 123 TBM cases, 400 pulmonary TB (pTB) cases and 477 healthy controls were genotyped on the MEGA array. A genome-wide association study (GWAS) comparing 114 TBM cases to 395 healthy controls showed no association with TBM susceptibility. A second analysis comparing 114 TBM cases to 382 pTB cases was conducted to investigate variants associated with different TB phenotypes. No significant associations were found with progression from pTB to TBM. Ten TBM cases and 10 healthy controls were exome sequenced. Gene set association tests SKAT-O and SKAT Common Rare were used to assess the association of rare SNPs and the cumulative effect of both common and rare SNPs with susceptibility to TBM, respectively. Ingenuity Pathway Analysis (IPA) of the top-hits of the SKAT-O analysis showed that NOD2 and CYP4F2 are both important in TBM pathogenesis and highlighted these as targets for future study. For the SKAT Common Rare analysis Centriolar Coiled-Coil Protein 110 (CCP110) was nominally associated (p = 5.89x10^-6) with TBM susceptibility. In addition, several top-hit genes ascribed to the development of the central nervous system (CNS) and innate immune system regulation were identified. Exome sequencing and GWAS of our TBM cohort has identified a single previously undescribed association of CCP110 with TBM susceptibility. These results advance our understanding of TBM in terms of both variants and genes that influence susceptibility. In addition, several candidate genes involved in innate immunity have been identified for further genotypic and functional investigation.

Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer's disease-associated genes: DTNB and DLG2

Alzheimer's disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency <0.01) associated with AD in a region-based, whole-genome sequencing (WGS) association study (rvGWAS) of two independent AD family datasets (NIMH/NIA; 2247 individuals; 605 families). Employing a sliding window approach across the genome, we identified several regions that achieved association p values <10^-6, using the burden test or the SKAT statistic. The genomic region around the dystobrevin beta (DTNB) gene was identified with the burden and SKAT test and replicated in case/control samples from the ADSP study reaching genome-wide significance after meta-analysis (p_meta = 4.74 × 10^-8). SKAT analysis also revealed region-based association around the Discs large homolog 2 (DLG2) gene and replicated in case/control samples from the ADSP study (p_meta = 1 × 10^-6). In conclusion, in a region-based rvGWAS of AD we identified two novel AD genes, DLG2 and DTNB, based on association with rare variants.

Gene set analysis with graph-embedded kernel association test

MOTIVATION

Kernel-based association test (KAT) has been a popular approach to evaluate the association of expressions of a gene set (e.g. pathway) with a phenotypic trait. KATs rely on kernel functions which capture the sample similarity across multiple features, to capture potential linear or non-linear relationship among features in a gene set. When calculating the kernel functions, no network graphical information about the features is considered. While genes in a functional group (e.g. a pathway) are not independent in general due to regulatory interactions, incorporating regulatory network (or graph) information can potentially increase the power of KAT. In this work, we propose a graph-embedded kernel association test, termed gKAT. gKAT incorporates prior pathway knowledge when constructing a kernel function into hypothesis testing.

RESULTS

We apply a diffusion kernel to capture any graph structures in a gene set, then incorporate such information to build a kernel function for further association test. We illustrate the geometric meaning of the approach. Through extensive simulation studies, we show that the proposed gKAT algorithm can improve testing power compared to the one without considering graph structures. Application to a real dataset further demonstrate the utility of the method.

AVAILABILITY AND IMPLEMENTATION

The R code used for the analysis can be accessed at https://github.com/JialinQu/gKAT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Systems biology analysis of human genomes points to key pathways conferring spina bifida risk

Genetic investigations of most structural birth defects, including spina bifida (SB), congenital heart disease, and craniofacial anomalies, have been underpowered for genome-wide association studies because of their rarity, genetic heterogeneity, incomplete penetrance, and environmental influences. Our systems biology strategy to investigate SB predisposition controls for population stratification and avoids much of the bias inherent in candidate gene searches that are pervasive in the field. We examine both protein coding and noncoding regions of whole genomes to analyze sequence variants, collapsed by gene or regulatory region, and apply machine learning, gene enrichment, and pathway analyses to elucidate molecular pathways and genes contributing to human SB.

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.

Deviation from baseline mutation burden provides powerful and robust rare-variants association test for complex diseases

Identifying rare variants that contribute to complex diseases is challenging because of the low statistical power in current tests comparing cases with controls. Here, we propose a novel and powerful rare variants association test based on the deviation of the observed mutation burden of a gene in cases from a baseline predicted by a weighted recursive truncated negative-binomial regression (RUNNER) on genomic features available from public data. Simulation studies show that RUNNER is substantially more powerful than state-of-the-art rare variant association tests and has reasonable type 1 error rates even for stratified populations or in small samples. Applied to real case-control data, RUNNER recapitulates known genes of Hirschsprung disease and Alzheimer's disease missed by current methods and detects promising new candidate genes for both disorders. In a case-only study, RUNNER successfully detected a known causal gene of amyotrophic lateral sclerosis. The present study provides a powerful and robust method to identify susceptibility genes with rare risk variants for complex diseases.

Investigating the Endo-Lysosomal System in Major Neurocognitive Disorders Due to Alzheimer's Disease, Frontotemporal Lobar Degeneration and Lewy Body Disease: Evidence for SORL1 as a Cross-Disease Gene

Dysfunctions in the endo-lysosomal system have been hypothesized to underlie neurodegeneration in major neurocognitive disorders due to Alzheimer's disease (AD), Frontotemporal Lobar Degeneration (FTLD), and Lewy body disease (DLB). The aim of this study is to investigate whether these diseases share genetic variability in the endo-lysosomal pathway. In AD, DLB, and FTLD patients and in controls (948 subjects), we performed a targeted sequencing of the top 50 genes belonging to the endo-lysosomal pathway. Genetic analyses revealed (i) four previously reported disease-associated variants in the SORL1 (p.N1246K, p.N371T, p.D2065V) and DNAJC6 genes (p.M133L) in AD, FTLD, and DLB, extending the previous knowledge attesting SORL1 and DNAJC6 as AD- and PD-related genes, respectively; (ii) three predicted null variants in AD patients in the SORL1 (p.R985X in early onset familial AD, p.R1207X) and PPT1 (p.R48X in early onset familial AD) genes, where loss of function is a known disease mechanism. A single variant and gene burden analysis revealed some nominally significant results of potential interest for SORL1 and DNAJC6 genes. Our data highlight that genes controlling key endo-lysosomal processes (i.e., protein sorting/transport, clathrin-coated vesicle uncoating, lysosomal enzymatic activity regulation) might be involved in AD, FTLD and DLB pathogenesis, thus suggesting an etiological link behind these diseases.

A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics

BACKGROUND

Recent genome-wide association studies (GWASs) have revealed the polygenic nature of psychiatric disorders and discovered a few of single-nucleotide polymorphisms (SNPs) associated with multiple psychiatric disorders. However, the extent and pattern of pleiotropy among distinct psychiatric disorders remain not completely clear.

METHODS

We analyzed 14 psychiatric disorders using summary statistics available from the largest GWASs by far. We first applied the cross-trait linkage disequilibrium score regression (LDSC) to estimate genetic correlation between disorders. Then, we performed a gene-based pleiotropy analysis by first aggregating a set of SNP-level associations into a single gene-level association signal using MAGMA. From a methodological perspective, we viewed the identification of pleiotropic associations across the entire genome as a high-dimensional problem of composite null hypothesis testing and utilized a novel method called PLACO for pleiotropy mapping. We ultimately implemented functional analysis for identified pleiotropic genes and used Mendelian randomization for detecting causal association between these disorders.

RESULTS

We confirmed extensive genetic correlation among psychiatric disorders, based on which these disorders can be grouped into three diverse categories. We detected a large number of pleiotropic genes including 5884 associations and 2424 unique genes and found that differentially expressed pleiotropic genes were significantly enriched in pancreas, liver, heart, and brain, and that the biological process of these genes was remarkably enriched in regulating neurodevelopment, neurogenesis, and neuron differentiation, offering substantial evidence supporting the validity of identified pleiotropic loci. We further demonstrated that among all the identified pleiotropic genes there were 342 unique ones linked with 6353 drugs with drug-gene interaction which can be classified into distinct types including inhibitor, agonist, blocker, antagonist, and modulator. We also revealed causal associations among psychiatric disorders, indicating that genetic overlap and causality commonly drove the observed co-existence of these disorders.

CONCLUSIONS

Our study is among the first large-scale effort to characterize gene-level pleiotropy among a greatly expanded set of psychiatric disorders and provides important insight into shared genetic etiology underlying these disorders. The findings would inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and pave the way to effective drug targets for clinical treatment.

Deep resequencing identifies candidate functional genes in leprosy GWAS loci

Leprosy is the second most prevalent mycobacterial disease globally. Despite the existence of an effective therapy, leprosy incidence has consistently remained above 200,000 cases per year since 2010. Numerous host genetic factors have been identified for leprosy that contribute to the persistently high case numbers. In the past decade, genetic epidemiology approaches, including genome-wide association studies (GWAS), identified more than 30 loci contributing to leprosy susceptibility. However, GWAS loci commonly encompass multiple genes, which poses a challenge to define causal candidates for each locus. To address this problem, we hypothesized that genes contributing to leprosy susceptibility differ in their frequencies of rare protein-altering variants between cases and controls. Using deep resequencing we assessed protein-coding variants for 34 genes located in GWAS or linkage loci in 555 Vietnamese leprosy cases and 500 healthy controls. We observed 234 nonsynonymous mutations in the targeted genes. A significant depletion of protein-altering variants was detected for the IL18R1 and BCL10 genes in leprosy cases. The IL18R1 gene is clustered with IL18RAP and IL1RL1 in the leprosy GWAS locus on chromosome 2q12.1. Moreover, in a recent GWAS we identified an HLA-independent signal of association with leprosy on chromosome 6p21. Here, we report amino acid changes in the CDSN and PSORS1C2 genes depleted in leprosy cases, indicating them as candidate genes in the chromosome 6p21 locus. Our results show that deep resequencing can identify leprosy candidate susceptibility genes that had been missed by classic linkage and association approaches.

A Kernel-based Test of Independence for Cluster-correlated Data

The Hilbert-Schmidt Independence Criterion (HSIC) is a powerful kernel-based statistic for assessing the generalized dependence between two multivariate variables. However, independence testing based on the HSIC is not directly possible for cluster-correlated data. Such a correlation pattern among the observations arises in many practical situations, e.g., family-based and longitudinal data, and requires proper accommodation. Therefore, we propose a novel HSIC-based independence test to evaluate the dependence between two multivariate variables based on cluster-correlated data. Using the previously proposed empirical HSIC as our test statistic, we derive its asymptotic distribution under the null hypothesis of independence between the two variables but in the presence of sample correlation. Based on both simulation studies and real data analysis, we show that, with clustered data, our approach effectively controls type I error and has a higher statistical power than competing methods.

Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes

Gene-based tests are valuable techniques for identifying genetic factors in complex traits. Here, we propose a gene-based testing framework that incorporates data on long-range chromatin interactions, several recent technical advances for region-based tests, and leverages the knockoff framework for synthetic genotype generation for improved gene discovery. Through simulations and applications to genome-wide association studies (GWAS) and whole-genome sequencing data for multiple diseases and traits, we show that the proposed test increases the power over state-of-the-art gene-based tests in the literature, identifies genes that replicate in larger studies, and can provide a more narrow focus on the possible causal genes at a locus by reducing the confounding effect of linkage disequilibrium. Furthermore, our results show that incorporating genetic variation in distal regulatory elements tends to improve power over conventional tests. Results for UK Biobank and BioBank Japan traits are also available in a publicly accessible database that allows researchers to query gene-based results in an easy fashion.

Enrichment of SARM1 alleles encoding variants with constitutively hyperactive NADase in patients with ALS and other motor nerve disorders

SARM1, a protein with critical NADase activity, is a central executioner in a conserved programme of axon degeneration. We report seven rare missense or in-frame microdeletion human SARM1 variant alleles in patients with amyotrophic lateral sclerosis (ALS) or other motor nerve disorders that alter the SARM1 auto-inhibitory ARM domain and constitutively hyperactivate SARM1 NADase activity. The constitutive NADase activity of these seven variants is similar to that of SARM1 lacking the entire ARM domain and greatly exceeds the activity of wild-type SARM1, even in the presence of nicotinamide mononucleotide (NMN), its physiological activator. This rise in constitutive activity alone is enough to promote neuronal degeneration in response to otherwise non-harmful, mild stress. Importantly, these strong gain-of-function alleles are completely patient-specific in the cohorts studied and show a highly significant association with disease at the single gene level. These findings of disease-associated coding variants that alter SARM1 function build on previously reported genome-wide significant association with ALS for a neighbouring, more common SARM1 intragenic single nucleotide polymorphism (SNP) to support a contributory role of SARM1 in these disorders. A broad phenotypic heterogeneity and variable age-of-onset of disease among patients with these alleles also raises intriguing questions about the pathogenic mechanism of hyperactive SARM1 variants.

Pleiotropy between language impairment and broader behavioral disorders-an investigation of both common and rare genetic variants

BACKGROUND

Language plays a major role in human behavior. For this reason, neurodevelopmental and psychiatric disorders in which linguistic ability is impaired could have a big impact on the individual's social interaction and general wellbeing. Such disorders tend to have a strong genetic component, but most past studies examined mostly the linguistic overlaps across these disorders; investigations into their genetic overlaps are limited. The aim of this study was to assess the potential genetic overlap between language impairment and broader behavioral disorders employing methods capturing both common and rare genetic variants.

METHODS

We employ polygenic risk scores (PRS) trained on specific language impairment (SLI) to evaluate genetic overlap across several disorders in a large case-cohort sample comprising ~13,000 autism spectrum disorder (ASD) cases, including cases of childhood autism and Asperger's syndrome, ~15,000 attention deficit/hyperactivity disorder (ADHD) cases, ~3000 schizophrenia cases, and ~21,000 population controls. We also examine rare variants in SLI/language-related genes in a subset of the sample that was exome-sequenced using the SKAT-O method.

RESULTS

We find that there is little evidence for genetic overlap between SLI and ADHD, schizophrenia, and ASD, the latter being in line with results of linguistic analyses in past studies. However, we observe a small, significant genetic overlap between SLI and childhood autism specifically, which we do not observe for SLI and Asperger's syndrome. Moreover, we observe that childhood autism cases have significantly higher SLI-trained PRS compared to Asperger's syndrome cases; these results correspond well to the linguistic profiles of both disorders. Our rare variant analyses provide suggestive evidence of association for specific genes with ASD, childhood autism, and schizophrenia.

CONCLUSIONS

Our study provides, for the first time, to our knowledge, genetic evidence for ASD subtypes based on risk variants for language impairment.

Insights on Genetic and Environmental Factors in Parkinson's Disease from a Regional Swedish Case-Control Cohort

Background:

Risk factors for Parkinson’s disease (PD) can be more or less relevant to a population due to population-specific genetic architecture, local lifestyle habits, and environmental exposures. Therefore, it is essential to study PD at a local, regional, and continental scale in order to increase the knowledge on disease etiology.

Objective:

We aimed to investigate the contribution of genetic and environmental factors to PD in a new Swedish case-control cohort.

Methods:

PD patients (n = 929) and matched population-based controls (n = 935) from the southernmost county in Sweden were included in the cohort. Information on environmental exposures was obtained using questionnaires at inclusion. Genetic analyses included a genome-wide association study (GWAS), haplotype assessment, and a risk profile analysis using cumulative genetic risk scores.

Results:

The cohort is a representative PD case-control cohort (64% men, mean age at diagnosis = 67 years, median Hoehn and Yahr score 2.0), in which previously reported associations between PD and environmental factors, such as tobacco, could be confirmed. We describe the first GWAS of PD solely composed of PD patients from Sweden, and confirm associations to well-established risk alleles in SNCA. In addition, we nominate an unconfirmed and potentially population-specific genome-wide significant association in the PLPP4 locus (rs12771445).

Conclusion:

This work provides an in-depth description of a new PD case-control cohort from southern Sweden, giving insights into environmental and genetic risk factors for PD in the Swedish population.

Predicting novel candidate human obesity genes and their site of action by systematic functional screening in Drosophila

The discovery of human obesity-associated genes can reveal new mechanisms to target for weight loss therapy. Genetic studies of obese individuals and the analysis of rare genetic variants can identify novel obesity-associated genes. However, establishing a functional relationship between these candidate genes and adiposity remains a significant challenge. We uncovered a large number of rare homozygous gene variants by exome sequencing of severely obese children, including those from consanguineous families. By assessing the function of these genes in vivo in Drosophila, we identified 4 genes, not previously linked to human obesity, that regulate adiposity (itpr, dachsous, calpA, and sdk). Dachsous is a transmembrane protein upstream of the Hippo signalling pathway. We found that 3 further members of the Hippo pathway, fat, four-jointed, and hippo, also regulate adiposity and that they act in neurons, rather than in adipose tissue (fat body). Screening Hippo pathway genes in larger human cohorts revealed rare variants in TAOK2 associated with human obesity. Knockdown of Drosophila tao increased adiposity in vivo demonstrating the strength of our approach in predicting novel human obesity genes and signalling pathways and their site of action.

Exome-Wide Pan-Cancer Analysis of Germline Variants in 8,719 Individuals Finds Little Evidence of Rare Variant Associations

BACKGROUND

Many cancer types show considerable heritability, and extensive research has been done to identify germline susceptibility variants. Linkage studies have discovered many rare high-risk variants, and genome-wide association studies (GWAS) have discovered many common low-risk variants. However, it is believed that a considerable proportion of the heritability of cancer remains unexplained by known susceptibility variants. The "rare variant hypothesis" proposes that much of the missing heritability lies in rare variants that cannot reliably be detected by linkage analysis or GWAS. Until recently, high sequencing costs have precluded extensive surveys of rare variants, but technological advances have now made it possible to analyze rare variants on a much greater scale.

OBJECTIVES

In this study, we investigated associations between rare variants and 14 cancer types.

METHODS

We ran association tests using whole-exome sequencing data from The Cancer Genome Atlas (TCGA) and validated the findings using data from the Pan-Cancer Analysis of Whole Genomes Consortium (PCAWG).

RESULTS

We identified four significant associations in TCGA, only one of which was replicated in PCAWG (BRCA1 and ovarian cancer).

CONCLUSIONS

Our results provide little evidence in favor of the rare variant hypothesis. Much larger sample sizes may be needed to detect undiscovered rare cancer variants.

Integration of DNA sequencing with population pharmacokinetics to improve the prediction of irinotecan exposure in cancer patients

BACKGROUND

Irinotecan (CPT-11) is an anticancer agent widely used to treat adult solid tumours. Large interindividual variability in the clearance of irinotecan and SN-38, its active and toxic metabolite, results in highly unpredictable toxicity.

METHODS

In 217 cancer patients treated with intravenous irinotecan single agent or in combination, germline DNA was used to interrogate the variation in 84 genes by next-generation sequencing. A stepwise analytical framework including a population pharmacokinetic model with SNP- and gene-based testing was used to identify demographic/clinical/genetic factors that influence the clearance of irinotecan and SN-38.

RESULTS

Irinotecan clearance was influenced by rs4149057 in SLCO1B1, body surface area, and co-administration of 5-fluorouracil/leucovorin/bevacizumab. SN-38 clearance was influenced by rs887829 in UGT1A1, pre-treatment total bilirubin, and EGFR rare variant burden. Within each UGT1A1 genotype group, elevated pre-treatment total bilirubin and/or presence of at least one rare variant in EGFR resulted in significantly lower SN-38 clearance. The model reduced the interindividual variability in irinotecan clearance from 38 to 34% and SN-38 clearance from 49 to 32%.

CONCLUSIONS

This new model significantly reduced the interindividual variability in the clearance of irinotecan and SN-38. New genetic factors of variability in clearance have been identified.

Whole-exome sequencing reveals a role of HTRA1 and EGFL8 in brain white matter hyperintensities

White matter hyperintensities (WMH) are among the most common radiological abnormalities in the ageing population and an established risk factor for stroke and dementia. While common variant association studies have revealed multiple genetic loci with an influence on their volume, the contribution of rare variants to the WMH burden in the general population remains largely unexplored. We conducted a comprehensive analysis of this burden in the UK Biobank using publicly available whole-exome sequencing data (n up to 17 830) and found a splice-site variant in GBE1, encoding 1,4-alpha-glucan branching enzyme 1, to be associated with lower white matter burden on an exome-wide level [c.691+2T>C, β = -0.74, standard error (SE) = 0.13, P = 9.7 × 10-9]. Applying whole-exome gene-based burden tests, we found damaging missense and loss-of-function variants in HTRA1 (frequency of 1 in 275 in the UK Biobank population) to associate with an increased WMH volume (P = 5.5 × 10-6, false discovery rate = 0.04). HTRA1 encodes a secreted serine protease implicated in familial forms of small vessel disease. Domain-specific burden tests revealed that the association with WMH volume was restricted to rare variants in the protease domain (amino acids 204-364; β = 0.79, SE = 0.14, P = 9.4 × 10-8). The frequency of such variants in the UK Biobank population was 1 in 450. The WMH volume was brought forward by ∼11 years in carriers of a rare protease domain variant. A comparison with the effect size of established risk factors for WMH burden revealed that the presence of a rare variant in the HTRA1 protease domain corresponded to a larger effect than meeting the criteria for hypertension (β = 0.26, SE = 0.02, P = 2.9 × 10-59) or being in the upper 99.8% percentile of the distribution of a polygenic risk score based on common genetic variants (β = 0.44, SE = 0.14, P = 0.002). In biochemical experiments, most (6/9) of the identified protease domain variants resulted in markedly reduced protease activity. We further found EGFL8, which showed suggestive evidence for association with WMH volume (P = 1.5 × 10-4, false discovery rate = 0.22) in gene burden tests, to be a direct substrate of HTRA1 and to be preferentially expressed in cerebral arterioles and arteries. In a phenome-wide association study mapping ICD-10 diagnoses to 741 standardized Phecodes, rare variants in the HTRA1 protease domain were associated with multiple neurological and non-neurological conditions including migraine with aura (odds ratio = 12.24, 95%CI: 2.54-35.25; P = 8.3 × 10-5]. Collectively, these findings highlight an important role of rare genetic variation and the HTRA1 protease in determining WMH burden in the general population.

Integrative eQTL-weighted hierarchical Cox models for SNP-set based time-to-event association studies

BACKGROUND

Integrating functional annotations into SNP-set association studies has been proven a powerful analysis strategy. Statistical methods for such integration have been developed for continuous and binary phenotypes; however, the SNP-set integrative approaches for time-to-event or survival outcomes are lacking.

METHODS

We here propose IEHC, an integrative eQTL (expression quantitative trait loci) hierarchical Cox regression, for SNP-set based survival association analysis by modeling effect sizes of genetic variants as a function of eQTL via a hierarchical manner. Three p-values combination tests are developed to examine the joint effects of eQTL and genetic variants after a novel decorrelated modification of statistics for the two components. An omnibus test (IEHC-ACAT) is further adapted to aggregate the strengths of all available tests.

RESULTS

Simulations demonstrated that the IEHC joint tests were more powerful if both eQTL and genetic variants contributed to association signal, while IEHC-ACAT was robust and often outperformed other approaches across various simulation scenarios. When applying IEHC to ten TCGA cancers by incorporating eQTL from relevant tissues of GTEx, we revealed that substantial correlations existed between the two types of effect sizes of genetic variants from TCGA and GTEx, and identified 21 (9 unique) cancer-associated genes which would otherwise be missed by approaches not incorporating eQTL.

CONCLUSION

IEHC represents a flexible, robust, and powerful approach to integrate functional omics information to enhance the power of identifying association signals for the survival risk of complex human cancers.

Gene-based mapping of trehalose biosynthetic pathway genes reveals association with source- and sink-related yield traits in a spring wheat panel

Trehalose 6‐phosphate (T6P) signalling regulates carbon use and allocation and is a target to improve crop yields. However, the specific contributions of trehalose phosphate synthase (TPS) and trehalose phosphate phosphatase (TPP) genes to source‐ and sink‐related traits remain largely unknown. We used enrichment capture sequencing on TPS and TPP genes to estimate and partition the genetic variation of yield‐related traits in a spring wheat (Triticum aestivum) breeding panel specifically built to capture the diversity across the 75,000 CIMMYT wheat cultivar collection. Twelve phenotypes were correlated to variation in TPS and TPP genes including plant height and biomass (source), spikelets per spike, spike growth and grain filling traits (sink) which showed indications of both positive and negative gene selection. Individual genes explained proportions of heritability for biomass and grain‐related traits. Three TPS1 homologues were particularly significant for trait variation. Epistatic interactions were found within and between the TPS and TPP gene families for both plant height and grain‐related traits. Gene‐based prediction improved predictive ability for grain weight when gene effects were combined with the whole‐genome markers. Our study has generated a wealth of information on natural variation of TPS and TPP genes related to yield potential which confirms the role for T6P in resource allocation and in affecting traits such as grain number and size confirming other studies which now opens up the possibility of harnessing natural genetic variation more widely to better understand the contribution of native genes to yield traits for incorporation into breeding programmes.

Unraveling the Genomic Architecture of the CYP3A Locus and ADME Genes for Personalized Tacrolimus Dosing

BACKGROUND

Tacrolimus (TAC) is an immunosuppressant widely prescribed following an allogenic organ transplant. Due to wide interindividual pharmacokinetic (PK) variability, optimizing TAC dosing based on genetic factors is required to minimize nephrotoxicity and acute rejections.

METHODS

We enrolled 1133 participants receiving TAC from 4 cohorts, consisting of 3 with kidney transplant recipients and 1 with healthy males from clinical trials. The effects of clinical factors were estimated to appropriately control confounding variables. A genome-wide association study, haplotype analysis, and a gene-based association test were conducted using the Korea Biobank Array or targeted sequencing for 114 pharmacogenes.

RESULTS

Genome-wide association study verified that CYP3A5*3 is the only common variant associated with TAC PK variability in Koreans. We detected several CYP3A5 and CYP3A4 rare variants that could potentially affect TAC metabolism. The haplotype structure of CYP3A5 stratified by CYP3A5*3 was a significant factor for CYP3A5 rare variant interpretation. CYP3A4 rare variant carriers among CYP3A5 intermediate metabolizers displayed higher TAC trough levels. Gene-based association tests in the 61 absorption, distribution, metabolism, and excretion genes revealed that CYP1A1 are associated with additional TAC PK variability: CYP1A1 rare variant carriers among CYP3A5 poor metabolizers showed lower TAC trough levels than the noncarrier controls.

CONCLUSIONS

Our study demonstrates that rare variant profiling of CYP3A5 and CYP3A4, combined with the haplotype structures of CYP3A locus, provide additive value for personalized TAC dosing. We also identified a novel association between CYP1A1 rare variants and TAC PK variability in the CYP3A5 nonexpressers that needs to be further investigated.

The role of vascular dementia associated genes in patients with Alzheimer's disease: A large case-control study in the Chinese population

Aim

The role of vascular dementia (VaD)‐associated genes in Alzheimer's disease (AD) remains elusive despite similar clinical and pathological features. We aimed to explore the relationship between these genes and AD in the Chinese population.

Methods

Eight VaD‐associated genes were screened by a targeted sequencing panel in a sample of 3604 individuals comprising 1192 AD patients and 2412 cognitively normal controls. Variants were categorized into common variants and rare variants according to minor allele frequency (MAF). Common variant (MAF ≥ 0.01)‐based association analysis was conducted by PLINK 1.9. Rare variant (MAF < 0.01) association study and gene‐based aggregation testing of rare variants were performed by PLINK 1.9 and Sequence Kernel Association Test‐Optimal (SKAT‐O test), respectively. Age at onset (AAO) and Mini‐Mental State Examination (MMSE) association studies were performed with PLINK 1.9. Analyses were adjusted for age, gender, and APOE ε4 status.

Results

Four common COL4A1 variants, including rs874203, rs874204, rs16975492, and rs1373744, exhibited suggestive associations with AD. Five rare variants, NOTCH3 rs201436750, COL4A1 rs747972545, COL4A1 rs201481886, CST3 rs765692764, and CST3 rs140837441, showed nominal association with AD risk. Gene‐based aggregation testing revealed that HTRA1 was nominally associated with AD. In the AAO and MMSE association studies, variants in GSN, ITM2B, and COL4A1 reached suggestive significance.

Conclusion

Common variants in COL4A1 and rare variants in HTRA1, NOTCH3, COL4A1, and CST3 may be implicated in AD pathogenesis. Besides, GSN, ITM2B, and COL4A1 are probably involved in the development of AD endophenotypes.

Paired comparisons of mutational profiles before and after brachytherapy in asian uveal melanoma patients

Uveal melanoma(UM) is the most common primary intraocular malignancy in adults. However, the incidence of UM in Asia is 10 to 20 times less than in Western populations. Therefore, for the first time, we report our whole exome sequencing (WES) data analysis to discover differences in the molecular features of Asian and Western UM, and to determine the disparities between the primary tumor before brachytherapy and enucleated samples after brachytherapy. WES of 19 samples (13 primary tumors, 5 enucleation samples after brachytherapy, and 1 liver metastasis) from 13 patients diagnosed with UM and treated between 2007 and 2019 at the Yonsei University Health System (YUHS) were analyzed using bioinformatics pipelines. We identified significantly altered genes in Asian UM and changes in mutational profiles before and after brachytherapy using various algorithms. GNAQ, BAP1, GNA11, SF3B1 and CYSLTR2 were significantly mutated in Asian UM, which is similar that reported frequently in previous Western-based UM studies. There were also similar copy number alterations (M3, 1p loss, 6p gain, 8q gain) in both groups. In paired comparisons of the same patients, DICER1 and LRP1B were distinctly mutated only in tumor samples obtained after brachytherapy using rare-variant association tests (P = 0.01, 0.01, respectively). The mutational profiles of Asian UM were generally similar to the data from previous Western-based studies. DICER1 and LRP1B were newly mutated genes with statistical significance in the regrowth samples after brachytherapy compared to the primary tumors, which may be related to resistance to brachytherapy.

Genetic factors in treatment-related cardiovascular complications in survivors of childhood acute lymphoblastic leukemia

Aim: Cardiovascular disease represents one of the main causes of secondary morbidity and mortality in patients with childhood cancer. Patients & methods: To further address this issue, we analyzed cardiovascular complications in relation to common and rare genetic variants derived through whole-exome sequencing from childhood acute lymphoblastic leukemia survivors (PETALE cohort). Results: Significant associations were detected among common variants in the TTN gene, left ventricular ejection fraction (p ≤ 0.0005), and fractional shortening (p ≤ 0.001). Rare variants enrichment in the NOS1, ABCG2 and NOD2 was observed in relation to left ventricular ejection fraction, and in NOD2 and ZNF267 genes in relation to fractional shortening. Following stratification according to risk groups, the modulatory effect of rare variants was additionally found in the CBR1, ABCC5 and AKR1C3 genes. None of the associations was replicated in St-Jude Lifetime Cohort Study. Conclusion: Further studies are needed to confirm whether the described genetic markers may be useful in identifying patients at increased risk of these complications.

Heterozygous loss of WBP11 function causes multiple congenital defects in humans and mice

The genetic causes of multiple congenital anomalies are incompletely understood. Here, we report novel heterozygous predicted loss-of-function (LoF) and predicted damaging missense variants in the WW domain binding protein 11 (WBP11) gene in seven unrelated families with a variety of overlapping congenital malformations, including cardiac, vertebral, tracheo-esophageal, renal and limb defects. WBP11 encodes a component of the spliceosome with the ability to activate pre-messenger RNA splicing. We generated a Wbp11 null allele in mouse using CRISPR-Cas9 targeting. Wbp11 homozygous null embryos die prior to E8.5, indicating that Wbp11 is essential for development. Fewer Wbp11 heterozygous null mice are found than expected due to embryonic and postnatal death. Importantly, Wbp11 heterozygous null mice are small and exhibit defects in axial skeleton, kidneys and esophagus, similar to the affected individuals, supporting the role of WBP11 haploinsufficiency in the development of congenital malformations in humans. LoF WBP11 variants should be considered as a possible cause of VACTERL association as well as isolated Klippel-Feil syndrome, renal agenesis or esophageal atresia.

Clinical and Genetic Analysis of Costa Rican Patients With Parkinson's Disease

Background: Most research in genomics of Parkinson's disease (PD) has been done in subjects of European ancestry, leading to sampling bias and leaving Latin American populations underrepresented. We sought to clinically characterize PD patients of Costa Rican origin and to sequence familial PD and atypical parkinsonism-associated genes in cases and controls.

Methods: We enrolled 118 PD patients with 97 unrelated controls. Collected information included demographics, exposure to risk and protective factors, and motor and cognitive assessments. We sequenced coding and untranslated regions in familial PD and atypical parkinsonism-associated genes including GBA, SNCA, VPS35, LRRK2, GCH1, PRKN, PINK1, DJ-1, VPS13C, and ATP13A2.

Results: Mean age of PD probands was 62.12 ± 13.51 years; 57.6% were male. The frequency of risk and protective factors averaged ~45%. Physical activity significantly correlated with better motor performance despite years of disease. Increased years of education were significantly associated with better cognitive function, whereas hallucinations, falls, mood disorders, and coffee consumption correlated with worse cognitive performance. We did not identify an association between tested genes and PD or any damaging homozygous or compound heterozygous variants. Rare variants in LRRK2 were nominally associated with PD; six were located between amino acids p.1620 and 1623 in the C-terminal-of-ROC (COR) domain of Lrrk2. Non-synonymous GBA variants (p.T369M, p.N370S, and p.L444P) were identified in three healthy individuals. One PD patient carried a pathogenic GCH1 variant, p.K224R.

Discussion: This is the first study that describes sociodemographics, risk factors, clinical presentation, and genetics of Costa Rican patients with PD, adding information to genomics research in a Latino population.

Whole exome sequencing in patients with Williams-Beuren syndrome followed by disease modeling in mice points to four novel pathways that may modify stenosis risk

Supravalvular aortic stenosis (SVAS) is a narrowing of the aorta caused by elastin (ELN) haploinsufficiency. SVAS severity varies among patients with Williams-Beuren syndrome (WBS), a rare disorder that removes one copy of ELN and 25-27 other genes. Twenty percent of children with WBS require one or more invasive and often risky procedures to correct the defect while 30% have no appreciable stenosis, despite sharing the same basic genetic lesion. There is no known medical therapy. Consequently, identifying genes that modify SVAS offers the potential for novel modifier-based therapeutics. To improve statistical power in our rare-disease cohort (N = 104 exomes), we utilized extreme-phenotype cohorting, functional variant filtration and pathway-based analysis. Gene set enrichment analysis of exome-wide association data identified increased adaptive immune system variant burden among genes associated with SVAS severity. Additional enrichment, using only potentially pathogenic variants known to differ in frequency between the extreme phenotype subsets, identified significant association of SVAS severity with not only immune pathway genes, but also genes involved with the extracellular matrix, G protein-coupled receptor signaling and lipid metabolism using both SKAT-O and RQTest. Complementary studies in Eln+/-; Rag1-/- mice, which lack a functional adaptive immune system, showed improvement in cardiovascular features of ELN insufficiency. Similarly, studies in mixed background Eln+/- mice confirmed that variations in genes that increase elastic fiber deposition also had positive impact on aortic caliber. By using tools to improve statistical power in combination with orthogonal analyses in mice, we detected four main pathways that contribute to SVAS risk.

Impact of natural selection on global patterns of genetic variation, and association with clinical phenotypes, at genes involved in SARS-CoV-2 infection

We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (ACE2, TMPRSS2, DPP4, and LY6E). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2, we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.

Common haplotypes at the CFH locus and low-frequency variants in CFHR2 and CFHR5 associate with systemic FHR concentrations and age-related macular degeneration

Age-related macular degeneration (AMD) is the principal cause of blindness in the elderly population. A strong effect on AMD risk has been reported for genetic variants at the CFH locus, encompassing complement factor H (CFH) and the complement-factor-H-related (CFHR) genes, but the underlying mechanisms are not fully understood. We aimed to dissect the role of factor H (FH) and FH-related (FHR) proteins in AMD in a cohort of 202 controls and 216 individuals with AMD. We detected elevated systemic levels of FHR-1 (p = 1.84 × 10-6), FHR-2 (p = 1.47 × 10-4), FHR-3 (p = 1.05 × 10-5) and FHR-4A (p = 1.22 × 10-2) in AMD, whereas FH concentrations remained unchanged. Common AMD genetic variants and haplotypes at the CFH locus strongly associated with FHR protein concentrations (e.g., FH p.Tyr402His and FHR-2 concentrations, p = 3.68 × 10-17), whereas the association with FH concentrations was limited. Furthermore, in an International AMD Genomics Consortium cohort of 17,596 controls and 15,894 individuals with AMD, we found that low-frequency and rare protein-altering CFHR2 and CFHR5 variants associated with AMD independently of all previously reported genome-wide association study (GWAS) signals (p = 5.03 × 10-3 and p = 2.81 × 10-6, respectively). Low-frequency variants in CFHR2 and CFHR5 led to reduced or absent FHR-2 and FHR-5 concentrations (e.g., p.Cys72Tyr in CFHR2 and FHR-2, p = 2.46 × 10-16). Finally, we showed localization of FHR-2 and FHR-5 in the choriocapillaris and in drusen. Our study identifies FHR proteins as key proteins in the AMD disease mechanism. Consequently, therapies that modulate FHR proteins might be effective for treating or preventing progression of AMD. Such therapies could target specific individuals with AMD on the basis of their genotypes at the CFH locus.

Whole genome sequencing identifies novel genetic mutations in patients with eczema herpeticum

BACKGROUND

Eczema herpeticum (EH) is a rare complication of atopic dermatitis (AD) caused by disseminated herpes simplex virus (HSV) infection. The role of rare and/or deleterious genetic variants in disease etiology is largely unknown. This study aimed to identify genes that harbor damaging genetic variants associated with HSV infection in AD with a history of recurrent eczema herpeticum (ADEH+).

METHODS

Whole genome sequencing (WGS) was performed on 49 recurrent ADEH+ (≥3 EH episodes), 491 AD without a history of eczema herpeticum (ADEH-) and 237 non-atopic control (NA) subjects. Variants were annotated, and a gene-based approach (SKAT-O) was used to identify genes harboring damaging genetic variants associated with ADEH+. Genes identified through WGS were studied for effects on HSV responses and keratinocyte differentiation.

RESULTS

Eight genes were identified in the comparison of recurrent ADEH+to ADEH-and NA subjects: SIDT2, CLEC7A, GSTZ1, TPSG1, SP110, RBBP8NL, TRIM15, and FRMD3. Silencing SIDT2 and RBBP8NL in normal human primary keratinocytes (NHPKs) led to significantly increased HSV-1 replication. SIDT2-silenced NHPKs had decreased gene expression of IFNk and IL1b in response to HSV-1 infection. RBBP8NL-silenced NHPKs had decreased gene expression of IFNk, but increased IL1b. Additionally, silencing SIDT2 and RBBP8NL also inhibited gene expression of keratinocyte differentiation markers keratin 10 (KRT10) and loricrin (LOR).

CONCLUSION

SIDT2 and RBBP8NL participate in keratinocyte's response to HSV-1 infection. SIDT2 and RBBP8NL also regulate expression of keratinocyte differentiation genes of KRT10 and LOR.

Multi-scale inference of genetic trait architecture using biologically annotated neural networks

In this article, we present Biologically Annotated Neural Networks (BANNs), a nonlinear probabilistic framework for association mapping in genome-wide association (GWA) studies. BANNs are feedforward models with partially connected architectures that are based on biological annotations. This setup yields a fully interpretable neural network where the input layer encodes SNP-level effects, and the hidden layer models the aggregated effects among SNP-sets. We treat the weights and connections of the network as random variables with prior distributions that reflect how genetic effects manifest at different genomic scales. The BANNs software uses variational inference to provide posterior summaries which allow researchers to simultaneously perform (i) mapping with SNPs and (ii) enrichment analyses with SNP-sets on complex traits. Through simulations, we show that our method improves upon state-of-the-art association mapping and enrichment approaches across a wide range of genetic architectures. We then further illustrate the benefits of BANNs by analyzing real GWA data assayed in approximately 2,000 heterogenous stock of mice from the Wellcome Trust Centre for Human Genetics and approximately 7,000 individuals from the Framingham Heart Study. Lastly, using a random subset of individuals of European ancestry from the UK Biobank, we show that BANNs is able to replicate known associations in high and low-density lipoprotein cholesterol content.

RBM20 is a candidate gene for hypertrophic cardiomyopathy

BACKGROUND

The genetic basis of a considerable fraction of hypertrophic cardiomyopathy (HCM) cases remains unknown. Whether the gene encoding RNA Binding Motif Protein 20 (RBM20) is implicated in HCM and the correlation of clinical characteristics of RBM20 heterozygotes with HCM remain unresolved. We aimed to investigate the association between RBM20 variants and HCM.

METHODS

We compared rare variants in the RBM20 gene by exome sequencing in 793 HCM patients and 414 healthy controls. Based on a case-control approach, we used SKAT-O to explore whether RBM20 is associated with HCM. The genetic distribution of RBM20 rare variants was then compared between HCM heterozygotes and dilated cardiomyopathy (DCM) heterozygotes. Clinical features and prognosis of RBM20 heterozygotes were compared with non-heterozygotes.

RESULTS

Gene-based association analysis implicated RBM20 as a susceptibility gene for developing HCM. Patients with RBM20 variants displayed a higher prevalence of sudden cardiac arrest (SCA) (6.7% vs. 0.9%, p = 0.001), increased sudden cardiac death (SCD) risk factor counts and impaired left ventricle systolic function. Further survival analysis revealed that RBM20 heterozygotes had higher incidences of resuscitated cardiac arrest, recurrent non-sustained ventricular tachycardia and malignant arrhythmias. Mendelian randomization suggested that RBM20 expression in left ventricle was causally associated with HCM and DCM with opposite effects.

CONCLUSIONS

This study identified RBM20 as a potential causal gene of HCM. RBM20 variants are associated with increased risk for SCA in HCM.

Impact of natural selection on global patterns of genetic variation, and association with clinical phenotypes, at genes involved in SARS-CoV-2 infection

We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection ( ACE2, TMPRSS2, DPP4 , and LY6E ). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2 , we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2 , we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.

Quantitative disease risk scores from EHR with applications to clinical risk stratification and genetic studies

Labeling clinical data from electronic health records (EHR) in health systems requires extensive knowledge of human expert, and painstaking review by clinicians. Furthermore, existing phenotyping algorithms are not uniformly applied across large datasets and can suffer from inconsistencies in case definitions across different algorithms. We describe here quantitative disease risk scores based on almost unsupervised methods that require minimal input from clinicians, can be applied to large datasets, and alleviate some of the main weaknesses of existing phenotyping algorithms. We show applications to phenotypic data on approximately 100,000 individuals in eMERGE, and focus on several complex diseases, including Chronic Kidney Disease, Coronary Artery Disease, Type 2 Diabetes, Heart Failure, and a few others. We demonstrate that relative to existing approaches, the proposed methods have higher prediction accuracy, can better identify phenotypic features relevant to the disease under consideration, can perform better at clinical risk stratification, and can identify undiagnosed cases based on phenotypic features available in the EHR. Using genetic data from the eMERGE-seq panel that includes sequencing data for 109 genes on 21,363 individuals from multiple ethnicities, we also show how the new quantitative disease risk scores help improve the power of genetic association studies relative to the standard use of disease phenotypes. The results demonstrate the effectiveness of quantitative disease risk scores derived from rich phenotypic EHR databases to provide a more meaningful characterization of clinical risk for diseases of interest beyond the prevalent binary (case-control) classification.

Rare Variants Analysis of Lysosomal Related Genes in Early-Onset and Familial Parkinson's Disease in a Chinese Cohort

BACKGROUND

Genetic studies have indicated that variants in several lysosomal genes are risk factors for idiopathic Parkinson's disease (PD). However, the role of lysosomal genes in PD in Asian populations is largely unknown.

OBJECTIVE

This study aimed to analyze rare variants in lysosomal related genes in Chinese population with early-onset and familial PD.

METHODS

In total, 1,136 participants, including 536 and 600 patients with sporadic early-onset PD (SEOPD) and familial PD, respectively, underwent whole-exome sequencing to assess the genetic etiology. Rare variants in PD were investigated in 67 candidate lysosomal related genes (LRGs), including 15 lysosomal function-related genes and 52 lysosomal storage disorder genes.

RESULTS

Compared with the autosomal dominant PD (ADPD) or SEOPD cohorts, a much higher proportion of patients with multiple rare damaging variants of LRGs were found in the autosomal recessive PD (ARPD) cohort. At a gene level, rare damaging variants in GBA and MAN2B1 were enriched in PD, but in SCARB2, MCOLN1, LYST, VPS16, and VPS13C were much less in patients. At an allele level, GBA p. Leu483Pro was found to increase the risk of PD. Genotype-phenotype correlation showed no significance in the clinical features among patients carrying a discrepant number of rare variants in LRGs.

CONCLUSION

Our study suggests rare variants in LRGs might be more important in the pathogenicity of ARPD cases compared with ADPD or SEOPD. We further confirm rare variants in GBA are involve in PD pathogenecity and other genes associated with PD identified in this study should be supported with more evidence.

Genetic Analysis of Functional Rare Germline Variants across Nine Cancer Types from an Electronic Health Record Linked Biobank

BACKGROUND

Rare variants play an essential role in the etiology of cancer. In this study, we aim to characterize rare germline variants that impact the risk of cancer.

METHODS

We performed a genome-wide rare variant analysis using germline whole exome sequencing (WES) data derived from the Geisinger MyCode initiative to discover cancer predisposition variants. The case-control association analysis was conducted by binning variants in 5,538 patients with cancer and 7,286 matched controls in a discovery set and 1,991 patients with cancer and 2,504 matched controls in a validation set across nine cancer types. Further, The Cancer Genome Atlas (TCGA) germline data were used to replicate the findings.

RESULTS

We identified 133 significant pathway-cancer pairs (85 replicated) and 90 significant gene-cancer pairs (12 replicated). In addition, we identified 18 genes and 3 pathways that were associated with survival outcome across cancers (Bonferroni P < 0.05).

CONCLUSIONS

In this study, we identified potential predisposition genes and pathways based on rare variants in nine cancers.

IMPACT

This work adds to the knowledge base and progress being made in precision medicine.

Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

A pan-cancer organoid platform for precision medicine

Patient-derived tumor organoids (TOs) are emerging as high-fidelity models to study cancer biology and develop novel precision medicine therapeutics. However, utilizing TOs for systems-biology-based approaches has been limited by a lack of scalable and reproducible methods to develop and profile these models. We describe a robust pan-cancer TO platform with chemically defined media optimized on cultures acquired from over 1,000 patients. Crucially, we demonstrate tumor genetic and transcriptomic concordance utilizing this approach and further optimize defined minimal media for organoid initiation and propagation. Additionally, we demonstrate a neural-network-based high-throughput approach for label-free, light-microscopy-based drug assays capable of predicting patient-specific heterogeneity in drug responses with applicability across solid cancers. The pan-cancer platform, molecular data, and neural-network-based drug assay serve as resources to accelerate the broad implementation of organoid models in precision medicine research and personalized therapeutic profiling programs.

Identification of Two Novel Candidate Genetic Variants Associated With the Responsiveness to Influenza Vaccination

Background

Annual vaccination is the most effective prevention of influenza infection. Up to now, a series of studies have demonstrated the role of genetic variants in regulating the antibody response to influenza vaccine. However, among the Chinese population, the relationship between genetic factors and the responsiveness to influenza vaccination has not been clarified through genome-wide association study (GWAS).

Method

A total of 1,968 healthy volunteers of Chinese descent were recruited and 1,582 of them were available for the subsequent two-stage analysis. In the discovery stage, according to our inclusion criteria, 123 of 1,582 subjects were selected as group 1 and received whole-genome sequencing to identify potential variants and genes. In the verification stage, 29 candidate variants identified by GWAS were selected for further validation in 481 subjects in group 2. Besides, we also analyzed nine variants from previously published reports in our study.

Results

Multivariate logistic regression analysis showed that compared with the TT genotype of ZBTB46 rs2281929, the TC + CC genotype was associated with a lower risk of low responsiveness to influenza vaccination adjusted for gender and age (Group 2: P = 7.75E-05, OR = 0.466, 95%CI = 0.319–0.680; Combined group: P = 1.18E-06, OR = 0.423, 95%CI = 0.299–0.599). In the combined group, IQGAP2 rs2455230 GC + CC genotype was correlated with a lower risk of low responsiveness to influenza vaccination compared with the GG genotype (P = 8.90E-04, OR = 0.535, 95%CI = 0.370–0.774), but the difference was not statistically significant in group 2 (P = 0.008). The antibody fold rises of subjects with ZBTB46 rs2281929 TT genotype against H1N1, H3N2,and B were all significantly lower than that of subjects with TC + CC genotype (P < 0.001). Compared with IQGAP2 rs2455230 GC + CC carriers, GG carriers had lower antibody fold rises to H1N1 (P = 0.001) and B (P = 0.032). The GG genotype of rs2455230 tended to be correlated with lower antibody fold rises (P = 0.096) against H3N2, but the difference was not statistically significant. No correlation was found between nine SNPs from previously published reports and the serological response to influenza vaccine in our study.

Conclusion

Our study identified two novel candidate missense variants, ZBTB46 rs2281929 and IQGAP2 rs2455230, were associated with the immune response to influenza vaccination among the Chinese population. Identifying these variants will provide more evidence for future research and improve the individualized influenza vaccination program.

Exome-based investigation of the genetic basis of human pigmentary glaucoma

Background

Glaucoma is a leading cause of visual disability and blindness. Release of iris pigment within the eye, pigment dispersion syndrome (PDS), can lead to one type of glaucoma known as pigmentary glaucoma. PDS has a genetic component, however, the genes involved with this condition are largely unknown. We sought to discover genes that cause PDS by testing cohorts of patients and controls for mutations using a tiered analysis of exome data.

Results

Our primary analysis evaluated melanosome-related genes that cause dispersion of iris pigment in mice (TYRP1, GPNMB, LYST, DCT, and MITF). We identified rare mutations, but they were not statistically enriched in PDS patients. Our secondary analyses examined PMEL (previously linked with PDS), MRAP, and 19 other genes. Four MRAP mutations were identified in PDS cases but not in controls (p = 0.016). Immunohistochemical analysis of human donor eyes revealed abundant MRAP protein in the iris, the source of pigment in PDS. However, analysis of MRAP in additional cohorts (415 cases and 1645 controls) did not support an association with PDS. We also did not confirm a link between PMEL and PDS in our cohorts due to lack of reported mutations and similar frequency of the variants in PDS patients as in control subjects.

Conclusions

We did not detect a statistical enrichment of mutations in melanosome-related genes in human PDS patients and we found conflicting data about the likely pathogenicity of MRAP mutations. PDS may have a complex genetic basis that is not easily unraveled with exome analyses.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07782-0.

Common and rare variant analyses combined with single-cell multiomics reveal cell-type-specific molecular mechanisms of COVID-19 severity

The determinants of severe COVID-19 in non-elderly adults are poorly understood, which limits opportunities for early intervention and treatment. Here we present novel machine learning frameworks for identifying common and rare disease-associated genetic variation, which outperform conventional approaches. By integrating single-cell multiomics profiling of human lungs to link genetic signals to cell-type-specific functions, we have discovered and validated over 1,000 risk genes underlying severe COVID-19 across 19 cell types. Identified risk genes are overexpressed in healthy lungs but relatively downregulated in severely diseased lungs. Genetic risk for severe COVID-19, within both common and rare variants, is particularly enriched in natural killer (NK) cells, which places these immune cells upstream in the pathogenesis of severe disease. Mendelian randomization indicates that failed NKG2D-mediated activation of NK cells leads to critical illness. Network analysis further links multiple pathways associated with NK cell activation, including type-I-interferon-mediated signalling, to severe COVID-19. Our rare variant model, PULSE, enables sensitive prediction of severe disease in non-elderly patients based on whole-exome sequencing; individualized predictions are accurate independent of age and sex, and are consistent across multiple populations and cohorts. Risk stratification based on exome sequencing has the potential to facilitate post-exposure prophylaxis in at-risk individuals, potentially based around augmentation of NK cell function. Overall, our study characterizes a comprehensive genetic landscape of COVID-19 severity and provides novel insights into the molecular mechanisms of severe disease, leading to new therapeutic targets and sensitive detection of at-risk individuals.

Rare CASP6N73T variant associated with hippocampal volume exhibits decreased proteolytic activity, synaptic transmission defect, and neurodegeneration

Caspase-6 (Casp6) is implicated in Alzheimer disease (AD) cognitive impairment and pathology. Hippocampal atrophy is associated with cognitive impairment in AD. Here, a rare functional exonic missense CASP6 single nucleotide polymorphism (SNP), causing the substitution of asparagine with threonine at amino acid 73 in Casp6 (Casp6N73T), was associated with hippocampal subfield CA1 volume preservation. Compared to wild type Casp6 (Casp6WT), recombinant Casp6N73T altered Casp6 proteolysis of natural substrates Lamin A/C and α-Tubulin, but did not alter cleavage of the Ac-VEID-AFC Casp6 peptide substrate. Casp6N73T-transfected HEK293T cells showed elevated Casp6 mRNA levels similar to Casp6WT-transfected cells, but, in contrast to Casp6WT, did not accumulate active Casp6 subunits nor show increased Casp6 enzymatic activity. Electrophysiological and morphological assessments showed that Casp6N73T recombinant protein caused less neurofunctional damage and neurodegeneration in hippocampal CA1 pyramidal neurons than Casp6WT. Lastly, CASP6 mRNA levels were increased in several AD brain regions confirming the implication of Casp6 in AD. These studies suggest that the rare Casp6N73T variant may protect against hippocampal atrophy due to its altered catalysis of natural protein substrates and intracellular instability thus leading to less Casp6-mediated damage to neuronal structure and function.

Scalable and Robust Regression Methods for Phenome-Wide Association Analysis on Large-Scale Biobank Data

With the advances in genotyping technologies and electronic health records (EHRs), large biobanks have been great resources to identify novel genetic associations and gene-environment interactions on a genome-wide and even a phenome-wide scale. To date, several phenome-wide association studies (PheWAS) have been performed on biobank data, which provides comprehensive insights into many aspects of human genetics and biology. Although inspiring, PheWAS on large-scale biobank data encounters new challenges including computational burden, unbalanced phenotypic distribution, and genetic relationship. In this paper, we first discuss these new challenges and their potential impact on data analysis. Then, we summarize approaches that are scalable and robust in GWAS and PheWAS. This review can serve as a practical guide for geneticists, epidemiologists, and other medical researchers to identify genetic variations associated with health-related phenotypes in large-scale biobank data analysis. Meanwhile, it can also help statisticians to gain a comprehensive and up-to-date understanding of the current technical tool development.