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

Association Study of TAF1 Variants in Parkinson’s Disease

Increasing evidence reveals sex as an important factor in the development of Parkinson’s disease (PD), but associations between genes on the sex chromosomes and PD remain unknown. TAF1 is a gene located on the X chromosome which is known to cause X-linked syndromic mental retardation-33 (MRXS33) and X-linked Dystonia-Parkinsonism (XDP). In this study, we conducted whole-exome sequencing (WES) among 1,917 patients with early-onset or familial PD and 1,652 controls in a Chinese population. We detected a hemizygous frameshift variant c.29_53dupGGA(CAG)₂CTACCATCA(CTG)₂C (p.A19Dfs*50) in two unrelated male patients. Further segregation analysis showed an unaffected family member carried this variant, which suggested the penetrance of the variant may be age-related and incomplete. To verify the effects of TAF1 on PD, genetic analyses were carried separately by gender. Analysis of rare variants by optimal sequence kernel association (SKAT-O) test showed a nominally significant difference in variant burden between the male PD patients and controls (2.01 vs. 1.38%, p = 0.027). In the female group, none of the variant types showed significant association with PD in this study. In conclusion, we found rare variants in TAF1 may be implicated in PD, but further genetic and functional analyses were needed.

Partitioning gene-level contributions to complex-trait heritability by allele frequency identifies disease-relevant genes

Recent works have shown that SNP heritability-which is dominated by low-effect common variants-may not be the most relevant quantity for localizing high-effect/critical disease genes. Here, we introduce methods to estimate the proportion of phenotypic variance explained by a given assignment of SNPs to a single gene ("gene-level heritability"). We partition gene-level heritability by minor allele frequency (MAF) to find genes whose gene-level heritability is explained exclusively by "low-frequency/rare" variants (0.5% ≤ MAF < 1%). Applying our method to ∼16K protein-coding genes and 25 quantitative traits in the UK Biobank (N = 290K "White British"), we find that, on average across traits, ∼2.5% of nonzero-heritability genes have a rare-variant component and only ∼0.8% (327 gene-trait pairs) have heritability exclusively from rare variants. Of these 327 gene-trait pairs, 114 (35%) were not detected by existing gene-level association testing methods. The additional genes we identify are significantly enriched for known disease genes, and we find several examples of genes that have been previously implicated in phenotypically related Mendelian disorders. Notably, the rare-variant component of gene-level heritability exhibits trends different from those of common-variant gene-level heritability. For example, while total gene-level heritability increases with gene length, the rare-variant component is significantly larger among shorter genes; the cumulative distributions of gene-level heritability also vary across traits and reveal differences in the relative contributions of rare/common variants to overall gene-level polygenicity. While nonzero gene-level heritability does not imply causality, if interpreted in the correct context, gene-level heritability can reveal useful insights into complex-trait genetic architecture.

Whole-genome sequencing reveals that variants in the Interleukin 18 Receptor Accessory Protein 3'UTR protect against ALS

The noncoding genome is substantially larger than the protein-coding genome but has been largely unexplored by genetic association studies. Here, we performed region-based rare variant association analysis of >25,000 variants in untranslated regions of 6,139 amyotrophic lateral sclerosis (ALS) whole genomes and the whole genomes of 70,403 non-ALS controls. We identified interleukin-18 receptor accessory protein (IL18RAP) 3' untranslated region (3'UTR) variants as significantly enriched in non-ALS genomes and associated with a fivefold reduced risk of developing ALS, and this was replicated in an independent cohort. These variants in the IL18RAP 3'UTR reduce mRNA stability and the binding of double-stranded RNA (dsRNA)-binding proteins. Finally, the variants of the IL18RAP 3'UTR confer a survival advantage for motor neurons because they dampen neurotoxicity of human induced pluripotent stem cell (iPSC)-derived microglia bearing an ALS-associated expansion in C9orf72, and this depends on NF-κB signaling. This study reveals genetic variants that protect against ALS by reducing neuroinflammation and emphasizes the importance of noncoding genetic association studies.

Evaluation of common and rare variants of Alzheimer's disease-causal genes in Parkinson's disease

INTRODUCTION

Parkinson's disease (PD) and Alzheimer's disease (AD) are the most common neurodegenerative diseases in the elderly. Recently, some variants of AD-causal genes (APP, PSEN1, PSEN2) have been reported in PD. In this study, we investigated the association between coding variants of AD-causal genes and PD in a large Chinese population cohort.

METHODS

We performed whole-exome sequencing (WES) on 1,917 patients with early-onset or familial PD and 1,652 controls, and whole-genome sequencing (WGS) on 1,962 sporadic late-onset PD and 1,279 controls. Genetic and phenotypic data were analyzed with regression analyses and the optimized sequence kernel association test. Further validation study was performed by Fisher's exact test.

RESULTS

We found that rs75733498 in the PSEN2 gene was significantly associated with early-onset or familial PD; however, no significant relationship was discovered between rs75733498 and sporadic late-onset PD. The result of the validation study still revealed a significant association between rs75733498 and PD. We observed a suggestive association with APP gene in early-onset or familial PD when considering damaging missense variants alone (p = 0.018) or combined with loss-of-function variants (p = 0.029). Further phenotypic analysis did not demonstrate any significant associations.

CONCLUSION

Our results support a possible genetic contribution of AD-causal genes to PD. These findings warrant further genetic and functional confirmation, and more powerful association studies will better decipher the mechanisms of PD.

Exome sequencing of individuals with Huntington's disease implicates FAN1 nuclease activity in slowing CAG expansion and disease onset

The age at onset of motor symptoms in Huntington's disease (HD) is driven by HTT CAG repeat length but modified by other genes. In this study, we used exome sequencing of 683 patients with HD with extremes of onset or phenotype relative to CAG length to identify rare variants associated with clinical effect. We discovered damaging coding variants in candidate modifier genes identified in previous genome-wide association studies associated with altered HD onset or severity. Variants in FAN1 clustered in its DNA-binding and nuclease domains and were associated predominantly with earlier-onset HD. Nuclease activities of purified variants in vitro correlated with residual age at motor onset of HD. Mutating endogenous FAN1 to a nuclease-inactive form in an induced pluripotent stem cell model of HD led to rates of CAG expansion similar to those observed with complete FAN1 knockout. Together, these data implicate FAN1 nuclease activity in slowing somatic repeat expansion and hence onset of HD.

Heteroplasmic mitochondrial DNA variants in cardiovascular diseases

Mitochondria are implicated in the pathogenesis of cardiovascular diseases (CVDs) but the reasons for this are not well understood. Maternally-inherited population variants of mitochondrial DNA (mtDNA) which affect all mtDNA molecules (homoplasmic) are associated with cardiometabolic traits and the risk of developing cardiovascular disease. However, it is not known whether mtDNA mutations only affecting a proportion of mtDNA molecules (heteroplasmic) also play a role. To address this question, we performed a high-depth (~1000-fold) mtDNA sequencing of blood DNA in 1,399 individuals with hypertension (HTN), 1,946 with ischemic heart disease (IHD), 2,146 with ischemic stroke (IS), and 723 healthy controls. We show that the per individual burden of heteroplasmic single nucleotide variants (mtSNVs) increases with age. The age-effect was stronger for low-level heteroplasmies (heteroplasmic fraction, HF, 5-10%), likely reflecting acquired somatic events based on trinucleotide mutational signatures. After correcting for age and other confounders, intermediate heteroplasmies (HF 10-95%) were more common in hypertension, particularly involving non-synonymous variants altering the amino acid sequence of essential respiratory chain proteins. These findings raise the possibility that heteroplasmic mtSNVs play a role in the pathophysiology of hypertension.

Associations of risk genes with onset age and plasma biomarkers of Alzheimer's disease: a large case-control study in mainland China

Most genetic studies concerning risk genes in Alzheimer's disease (AD) are from Caucasian populations, whereas the data remain limited in the Chinese population. In this study, we systematically explored the relationship between AD and risk genes in mainland China. We sequenced 33 risk genes previously reported to be associated with AD in a total of 3604 individuals in the mainland Chinese population. Common variant (MAF ≥ 0.01) based association analysis and gene-based (MAF < 0.01) association test were performed by PLINK 1.9 and Sequence Kernel Association Test-Optimal, respectively. Polygenic risk score (PRS) was calculated, and receiver operating characteristic curve (AUC) was computed. Plasma Aβ42, Aβ40, total tau (T-tau), and neurofilament light chain (NFL) were tested in a subgroup, and their associations with PRS were conducted using the Spearman correlation test. Six common variants varied significantly between AD patients and cognitively normal controls after the adjustment of age, gender, and APOE ε4 status, including variants in ABCA7 (n = 5) and APOE (n = 1). Among them, four variants were novel and two were reported previously. The AUC of PRS was 0.71. The high PRS was significantly associated with an earlier age at onset (P = 4.30 × 10-4). PRS was correlated with plasma Aβ42, Aβ42/Aβ40 ratio, T-tau, and NFL levels. Gene-based association test revealed that ABCA7 and UNC5C reached statistical significance. The common variants in APOE and ABCA7, as well as rare variants in ABCA7 and UNC5C, may contribute to the etiology of AD. Moreover, the PRS, to some extent, could predict the risk, onset age, and biological changes of AD.

Arrhythmia Variant Associations and Reclassifications in the eMERGE-III Sequencing Study

BACKGROUND

Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability.

METHODS

The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record-derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells.

RESULTS

As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP.

CONCLUSIONS

Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier; NCT03394859.

Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.

GenRisk: A tool for comprehensive genetic risk modeling

Summary

The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here, we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants-based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats.

Availability and implementation

GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk).

Supplementary information

Supplementary data are available at Bioinformatics online.

Speeding up Monte Carlo simulations for the adaptive sum of powered score test with importance sampling

A central but challenging problem in genetic studies is to test for (usually weak) associations between a complex trait (e.g., a disease status) and sets of multiple genetic variants. Due to the lack of a uniformly most powerful test, data-adaptive tests, such as the adaptive sum of powered score (aSPU) test, are advantageous in maintaining high power against a wide range of alternatives. However, there is often no closed-form to accurately and analytically calculate the p-values of many adaptive tests like aSPU, thus Monte Carlo (MC) simulations are often used, which can be time consuming to achieve a stringent significance level (e.g., 5e-8) used in genome-wide association studies (GWAS). To estimate such a small p-value, we need a huge number of MC simulations (e.g., 1e+10). As an alternative, we propose using importance sampling to speed up such calculations. We develop some theory to motivate a proposed algorithm for the aSPU test, and show that the proposed method is computationally more efficient than the standard MC simulations. Using both simulated and real data, we demonstrate the superior performance of the new method over the standard MC simulations.

Multivariate, region-based genetic analyses of facets of reproductive aging in White and Black women

BACKGROUND

Age at final menstrual period (FMP) and the accompanying hormone trajectories across the menopause transition do not occur in isolation, but likely share molecular pathways. Understanding the genetics underlying the endocrinology of the menopause transition may be enhanced by jointly analyzing multiple interrelated traits.

METHODS

In a sample of 347 White and 164 Black women from the Study of Women's Health Across the Nation (SWAN), we investigated pleiotropic effects of 54 candidate genetic regions of interest (ROI) on 5 menopausal traits (age at FMP and premenopausal and postmenopausal levels of follicle stimulation hormone and estradiol) using multivariate kernel regression (Multi-SKAT). A backward elimination procedure was used to identify which subset of traits were most strongly associated with a specific ROI.

RESULTS

In White women, the 20 kb ROI around rs10734411 was significantly associated with the multivariate distribution of age at FMP, premenopausal estradiol, and postmenopausal estradiol (omnibus p-value = .00004). This association did not replicate in the smaller sample of Black women.

CONCLUSION

This study using a region-based, multiple-trait approach suggests a shared genetic basis among multiple facets of reproductive aging.

CELSR1 Risk Alleles in Familial Bicuspid Aortic Valve and Hypoplastic Left Heart Syndrome

BACKGROUND

Whole-genome sequencing in families enables deciphering of congenital heart disease causes. A shared genetic basis for familial bicuspid aortic valve (BAV) and hypoplastic left heart syndrome (HLHS) was postulated.

METHODS

Whole-genome sequencing was performed in affected members of 6 multiplex BAV families, an HLHS cohort of 197 probands and 546 relatives, and 813 controls. Data were filtered for rare, predicted-damaging variants that cosegregated with familial BAV and disrupted genes associated with congenital heart disease in humans and mice. Candidate genes were further prioritized by rare variant burden testing in HLHS cases versus controls. Modifier variants in HLHS proband-parent trios were sought to account for the severe developmental phenotype.

RESULTS

In 5 BAV families, missense variants in 6 ontologically diverse genes for structural (SPTBN1, PAXIP1, and FBLN1) and signaling (CELSR1, PLXND1, and NOS3) proteins fulfilled filtering metrics. CELSR1, encoding cadherin epidermal growth factor laminin G seven-pass G-type receptor, was identified as a candidate gene in 2 families and was the only gene demonstrating rare variant enrichment in HLHS probands (P=0.003575). HLHS-associated CELSR1 variants included 16 missense, one splice site, and 3 noncoding variants predicted to disrupt canonical transcription factor binding sites, most of which were inherited from a parent without congenital heart disease. Filtering whole-genome sequencing data for rare, predicted-damaging variants inherited from the other parent revealed 2 cases of CELSR1 compound heterozygosity, one case of CELSR1-CELSR3 synergistic heterozygosity, and 4 cases of CELSR1-MYO15A digenic heterozygosity.

CONCLUSIONS

CELSR1 is a susceptibility gene for familial BAV and HLHS, further implicating planar cell polarity pathway perturbation in congenital heart disease.

Molecular tools for the genomic assessment of oocyte’s reproductive competence

The most important factor associated with oocytes' developmental competence has been widely identified as the presence of chromosomal abnormalities. However, growing application of genome-wide sequencing (GS) in population diagnostics has enabled the identification of multifactorial genetic predispositions to sub-lethal pathologies, including those affecting IVF outcomes and reproductive fitness. Indeed, GS analysis in families with history of isolated infertility has recently led to the discovery of new genes and variants involved in specific human infertility endophenotypes that impact the availability and the functionality of female gametes by altering unique mechanisms necessary for oocyte maturation and early embryo development. Ongoing advancements in analytical and bioinformatic pipelines for the study of the genetic determinants of oocyte competence may provide the biological evidence required not only for improving the diagnosis of isolated female infertility but also for the development of novel preventive and therapeutic approaches for reproductive failure. Here, we provide an updated discussion and review of the progresses made in preconception genomic medicine in the identification of genetic factors associated with oocyte availability, function, and competence.

Comparison of mixed model based approaches for correcting for population substructure with application to extreme phenotype sampling

Background

Mixed models are used to correct for confounding due to population stratification and hidden relatedness in genome-wide association studies. This class of models includes linear mixed models and generalized linear mixed models. Existing mixed model approaches to correct for population substructure have been previously investigated with both continuous and case-control response variables. However, they have not been investigated in the context of extreme phenotype sampling (EPS), where genetic covariates are only collected on samples having extreme response variable values. In this work, we compare the performance of existing binary trait mixed model approaches (GMMAT, LEAP and CARAT) on EPS data. Since linear mixed models are commonly used even with binary traits, we also evaluate the performance of a popular linear mixed model implementation (GEMMA).

Results

We used simulation studies to estimate the type I error rate and power of all approaches assuming a population with substructure. Our simulation results show that for a common candidate variant, both LEAP and GMMAT control the type I error rate while CARAT’s rate remains inflated. We applied all methods to a real dataset from a Québec, Canada, case-control study that is known to have population substructure. We observe similar type I error control with the analysis on the Québec dataset. For rare variants, the false positive rate remains inflated even after correction with mixed model approaches. For methods that control the type I error rate, the estimated power is comparable.

Conclusions

The methods compared in this study differ in their type I error control. Therefore, when data are from an EPS study, care should be taken to ensure that the models underlying the methodology are suitable to the sampling strategy and to the minor allele frequency of the candidate SNPs.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08297-y).

Contribution of Rare Genetic Variation to Disease Susceptibility in a Large Scandinavian Myositis Cohort

OBJECTIVE

Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of complex autoimmune conditions characterized by inflammation in skeletal muscle and extramuscular compartments, and interferon (IFN) system activation. We undertook this study to examine the contribution of genetic variation to disease susceptibility and to identify novel avenues for research in IIMs.

METHODS

Targeted DNA sequencing was used to mine coding and potentially regulatory single nucleotide variants from ~1,900 immune-related genes in a Scandinavian case-control cohort of 454 IIM patients and 1,024 healthy controls. Gene-based aggregate testing, together with rare variant- and gene-level enrichment analyses, was implemented to explore genotype-phenotype relations.

RESULTS

Gene-based aggregate tests of all variants, including rare variants, identified IFI35 as a potential genetic risk locus for IIMs, suggesting a genetic signature of type I IFN pathway activation. Functional annotation of the IFI35 locus highlighted a regulatory network linked to the skeletal muscle-specific gene PTGES3L, as a potential candidate for IIM pathogenesis. Aggregate genetic associations with AGER and PSMB8 in the major histocompatibility complex locus were detected in the antisynthetase syndrome subgroup, which also showed a less marked genetic signature of the type I IFN pathway. Enrichment analyses indicated a burden of synonymous and noncoding rare variants in IIM patients, suggesting increased disease predisposition associated with these classes of rare variants.

CONCLUSION

Our study suggests the contribution of rare genetic variation to disease susceptibility in IIM and specific patient subgroups, and pinpoints genetic associations consistent with previous findings by gene expression profiling. These features highlight genetic profiles that are potentially relevant to disease pathogenesis.

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

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.