Rare Variant Association Research Articles

Rare genetic variation implicated in non-Hispanic white families with Alzheimer disease.

ObjectiveTo identify genetic variation influencing late-onset Alzheimer disease (LOAD), we used a large data set of non-Hispanic white (NHW) extended families multiply-affected by LOAD by performing whole genome sequencing (WGS).MethodsAs part of the Alzheimer Disease Sequencing Project, WGS data were generated for 197 NHW participants from 42 families (affected individuals and unaffected, elderly relatives). A two-pronged approach was taken. First, variants were prioritized using heterogeneity logarithm of the odds (HLOD) and family-specific LOD scores as well as annotations based on function, frequency, and segregation with disease. Second, known Alzheimer disease (AD) candidate genes were assessed for rare variation using a family-based association test.ResultsWe identified 41 rare, predicted-damaging variants that segregated with disease in the families that contributed to the HLOD or family-specific LOD regions. These included a variant in nitric oxide synthase 1 adaptor protein that segregates with disease in a family with 7 individuals with AD, as well as variants in RP11-433J8, ABCA1, and FISP2. Rare-variant association identified 2 LOAD candidate genes associated with disease in these families: FERMT2 (p-values = 0.001) and SLC24A4 (p-value = 0.009). These genes still showed association while controlling for common index variants, indicating the rare-variant signal is distinct from common variation that initially identified the genes as candidates.ConclusionsWe identified multiple genes with putative damaging rare variants that segregate with disease in multiplex AD families and showed that rare variation may influence AD risk at AD candidate genes. These results identify novel AD candidate genes and show a role for rare variation in LOAD etiology, even at genes previously identified by common variation.

Allele balance bias identifies systematic genotyping errors and false disease associations.

In recent years, next‐generation sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors, and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the AB distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state‐of‐the‐art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies. Availability: https://github.com/Francesc-Muyas/ABB.

ProxECAT: Proxy External Controls Association Test. A new case-control gene region association test using allele frequencies from public controls.

A primary goal of the recent investment in sequencing is to detect novel genetic associations in health and disease improving the development of treatments and playing a critical role in precision medicine. While this investment has resulted in an enormous total number of sequenced genomes, individual studies of complex traits and diseases are often smaller and underpowered to detect rare variant genetic associations. Existing genetic resources such as the Exome Aggregation Consortium (>60,000 exomes) and the Genome Aggregation Database (~140,000 sequenced samples) have the potential to be used as controls in these studies. Fully utilizing these and other existing sequencing resources may increase power and could be especially useful in studies where resources to sequence additional samples are limited. However, to date, these large, publicly available genetic resources remain underutilized, or even misused, in large part due to the lack of statistical methods that can appropriately use this summary level data. Here, we present a new method to incorporate external controls in case-control analysis called ProxECAT (Proxy External Controls Association Test). ProxECAT estimates enrichment of rare variants within a gene region using internally sequenced cases and external controls. We evaluated ProxECAT in simulations and empirical analyses of obesity cases using both low-depth of coverage (7x) whole-genome sequenced controls and ExAC as controls. We find that ProxECAT maintains the expected type I error rate with increased power as the number of external controls increases. With an accompanying R package, ProxECAT enables the use of publicly available allele frequencies as external controls in case-control analysis.

Imputation-Aware Tag SNP Selection To Improve Power for Large-Scale, Multi-ethnic Association Studies.

The emergence of very large cohorts in genomic research has facilitated a focus on genotype-imputation strategies to power rare variant association. These strategies have benefited from improvements in imputation methods and association tests, however little attention has been paid to ways in which array design can increase rare variant association power. Therefore, we developed a novel framework to select tag SNPs using the reference panel of 26 populations from Phase 3 of the 1000 Genomes Project. We evaluate tag SNP performance via mean imputed r2 at untyped sites using leave-one-out internal validation and standard imputation methods, rather than pairwise linkage disequilibrium. Moving beyond pairwise metrics allows us to account for haplotype diversity across the genome for improve imputation accuracy and demonstrates population-specific biases from pairwise estimates. We also examine array design strategies that contrast multi-ethnic cohorts vs. single populations, and show a boost in performance for the former can be obtained by prioritizing tag SNPs that contribute information across multiple populations simultaneously. Using our framework, we demonstrate increased imputation accuracy for rare variants (frequency < 1%) by 0.5–3.1% for an array of one million sites and 0.7–7.1% for an array of 500,000 sites, depending on the population. Finally, we show how recent explosive growth in non-African populations means tag SNPs capture on average 30% fewer other variants than in African populations. The unified framework presented here will enable investigators to make informed decisions for the design of new arrays, and help empower the next phase of rare variant association for global health.

Identification of a Genomic Region between SLC29A1 and HSP90AB1 Associated with Risk of Bevacizumab-Induced Hypertension: CALGB 80405 (Alliance).

Purpose: Bevacizumab is a VEGF-specific angiogenesis inhibitor indicated as an adjunct to chemotherapy for the treatment of multiple cancers. Hypertension is commonly observed during bevacizumab treatment, and high-grade toxicity can limit therapy or lead to cardiovascular complications. The factors that contribute to interindividual variability in blood pressure rise during bevacizumab treatment are not well understood.Experimental Design: To identify genomic regions associated with bevacizumab-induced hypertension risk, sequencing of candidate genes and flanking regulatory regions was performed on 61 patients treated with bevacizumab (19 cases developed early-onset grade 3 hypertension and 42 controls had no reported hypertension in the first six cycles of treatment). SNP-based tests for common variant associations and gene-based tests for rare variant associations were performed in 174 candidate genes.Results: Four common variants in independent linkage disequilibrium blocks between SLC29A1 and HSP90AB1 were among the top associations. Validation in larger bevacizumab-treated cohorts supported association between rs9381299 with early grade 3+ hypertension (P = 0.01; OR, 2.4) and systolic blood pressure >180 mm Hg (P = 0.02; OR, 2.1). rs834576 was associated with early grade 3+ hypertension in CALGB 40502 (P = 0.03; OR, 2.9). These SNP regions are enriched for regulatory elements that may potentially increase gene expression. In vitro overexpression of SLC29A1 in human endothelial cells disrupted adenosine signaling and reduced nitric oxide levels that were further lowered upon bevacizumab exposure.Conclusions: The genomic region between SLC29A1 and HSP90AB1 and its role in regulating adenosine signaling are key targets for further investigation into the pathogenesis of bevacizumab-induced hypertension. Clin Cancer Res; 24(19); 4734-44. ©2018 AACR.

Common and rare GCH1 variants are associated with Parkinson'sdisease.

GCH1 encodes the enzyme guanosine triphospahte (GTP) cyclohydrolase 1, essential for dopamine synthesis in nigrostriatal cells, and rare mutations in GCH1 may lead to Dopa-responsive dystonia (DRD). While GCH1 is implicated in genomewide association studies in Parkinson's disease (PD), only a few studies examined the role of rare GCH1 variants in PD, with conflicting results. In the present study, GCH1 and its 5' and 3' untranslated regions were sequenced in 1113 patients with PD and 1111 controls. To examine the association of rare GCH1 variants with PD, burden analysis was performed. Three rare GCH1 variants, which were previously reported to be pathogenic in DRD, were found in five patients with PD and not in controls (sequence Kernel association test, p= 0.024). A common haplotype, tagged by rs841, was associated with a reduced risk for PD (OR= 0.71, 95% CI= 0.61-0.83, p= 1.24× 10-4), and with increased GCH1 expression in brain regions relevant for PD (www.gtexportal.org). Our results support a role for rare, DRD-related variants, and common GCH1 variants in the pathogenesis ofPD.

General retrospective mega‐analysis framework for rare variant association tests

Here, we describe a retrospective mega-analysis framework for gene- or region-based multimarker rare variant association tests. Our proposed mega-analysis association tests allow investigators to combine longitudinal and cross-sectional family- and/or population-based studies. This framework can be applied to a continuous, categorical, or survival trait. In addition to autosomal variants, the tests can be applied to conduct mega-analyses on X-chromosome variants. Tests were built on study-specific region- or gene-level quasiscore statistics and, therefore, do not require estimates of effects of individual rare variants. We used the generalized estimating equation approach to account for complex multiple correlation structures between family members, repeated measurements, and genetic markers. While accounting for multilevel correlations and heterogeneity across studies, the test statistics were computationally efficient and feasible for large-scale sequencing studies. The retrospective aspect of association tests helps alleviate bias due to phenotype-related sampling and type I errors due to misspecification of phenotypic distribution. We evaluated our developed mega-analysis methods through comprehensive simulations with varying sample sizes, covariates, population stratification structures, and study designs across multiple studies. To illustrate application of the proposed framework, we conducted a mega-association analysis combining a longitudinal family study and a cross-sectional case-control study from Genetic Analysis Workshop 19.

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits—plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia.

PTGIS is a Novel Susceptibility Gene for Pulmonary Arterial Hypertension

Background: Genetic variants such as inactivating mutation in the bone morphogenetic protein receptor 2 (BMPR2) gene account for approximately 15-20% of the etiology of idiopathic pulmonary arterial hypertension (IPAH). Increasing evidence indicates the existence of other IPAH susceptibility genes. Methods: The whole-genome sequencing was performed in a discovery cohort including 42 IPAH patients who are lacking BMPR2 mutations. Putative IPAH genes were validated in an independent cohort that included 188 IPAH patients and 968 healthy controls. Functional assessments were conducted to analyze the effects of candidate genetic variants on transcript splicing, enzymatic activity and function. Results: An enrichment of rare variants in the gene encoding prostacyclin synthase (PTGIS) was initially identified by the whole-genome sequencing. The association of PTGIS rare variants with IPAH was confirmed in the replication cohort. In total, fourteen patients (6.1%) were heterozygous for three PTGIS rare variants, including one splice-site variant (c.521 1G>A) and two missense variants (R252Q, A447T). These rare variants conferred a 7.8-fold greater risk of IPAH (95% confidence interval (CI), 3.2 to 18.8; P=5 x 10-6). Inhaled iloprost induced more significantly decrease of pulmonary vascular resistance (P=0.001) and increase of cardiac index (P A variant resulted in aberrant mRNA transcripts. The functional studies showed that the two missense variants caused a decrease in prostacyclin production and increased cell death in pulmonary microvascular endothelial cells. Conclusions: We have identified three loss-of-function rare variants in the PTGIS gene from two independent IPAH cohorts. The genetic variants of PTGIS predispose pulmonary vascular responses to the iloprost stimulation and cause deleterious effects. These results provide a novel finding that PTGIS rare variants are involved in the pathogenesis of IPAH. Funding: The work was supported by the following grants: the Beijing Natural Science Foundation (7181009, 7172180), the National Natural Science Foundation of China (81320108005), the National Science Fund for Distinguished Young Scholars (81425002), CAMS Innovation Fund for Medical Sciences (2016-I2M-1-002, 2016-I2M-4-003), the National Key Research and Development Program of China (2016YFC0901502), Sanming Project of Medicine in Shenzhen-Professor Zhi-Cheng Jing's Group for Precise Medicine Research in Thrombosis and Vascular Disease (SZSM201502001) , and the fund from State Key Laboratory of Cardiovascular Disease (2016-kf04, 2018ZR-02). Declaration of Interest: The authors declare no competing financial interests. Ethical Approval: The study protocol was approved by the ethics committees of Shanghai Pulmonary Hospital and FuWai Hospital. The participants, who were all of Chinese Han ancestry, provided written informed consent.

Testing an optimally weighted combination of common and/or rare variants with multiple traits.

Recently, joint analysis of multiple traits has become popular because it can increase statistical power to identify genetic variants associated with complex diseases. In addition, there is increasing evidence indicating that pleiotropy is a widespread phenomenon in complex diseases. Currently, most of existing methods test the association between multiple traits and a single genetic variant. However, these methods by analyzing one variant at a time may not be ideal for rare variant association studies because of the allelic heterogeneity as well as the extreme rarity of rare variants. In this article, we developed a statistical method by testing an optimally weighted combination of variants with multiple traits (TOWmuT) to test the association between multiple traits and a weighted combination of variants (rare and/or common) in a genomic region. TOWmuT is robust to the directions of effects of causal variants and is applicable to different types of traits. Using extensive simulation studies, we compared the performance of TOWmuT with the following five existing methods: gene association with multiple traits (GAMuT), multiple sequence kernel association test (MSKAT), adaptive weighting reverse regression (AWRR), single-TOW, and MANOVA. Our results showed that, in all of the simulation scenarios, TOWmuT has correct type I error rates and is consistently more powerful than the other five tests. We also illustrated the usefulness of TOWmuT by analyzing a whole-genome genotyping data from a lung function study.

Whole Genome Sequence Association Analysis and Diabetes-centric Functional Annotation of Type 2 Diabetes

Our understanding of the genetic basis of T2D has been significantly advanced by identification of T2D loci through analysis of common variation; however, evidence suggests a role for rare regulatory variation influencing T2D. We leveraged the largest available whole genome sequence (WGS) data from NHLBI’s Trans-Omics for Precision Medicine (TOPMed) initiative and diabetes-centric genomic function data to the interpretation of results. We performed single-variant pooled-ancestry association analyses with (&amp;gt;30x deep sequence) WGS in 13,200 individuals (2,601 T2D and 10,599 controls) from 6 studies. The association analyses were performed in the Analysis Commons hosted on DNANexus. We demonstrated the utility of the OASIS (Omics Analysis, Search and Information System) platform and integrating diabetes-specific functional annotation in a recently discovered locus (GIP-IGF2BP1) to fine-map to the likely causal variants. Our results identified common (minor allele frequency [MAF] &amp;gt; 0.05) variant associations (P &amp;lt; 5 × 10-8) at a known locus with T2D: TCF7L2 (rs7903146, P = 3.8 × 10-12). We also identified a potentially novel association on Chr15q21 with 27 rare variants (MAF = 0.2%, P =1.3 × 10-8, r2=1) spanning a 7.5 MB region. In the Old Order Amish study, 53 individuals carry the haplotype tagged by these 27 variants; 17% of carriers are diagnosed with T2D compared to 3% of the non-carriers. Interrogation of the GIP-IGF2BP1 locus, utilizing diabetes-specific annotation and association evidence of both common and rare non-coding variants, within the OASIS browser implicated nearby genes in the region as being the likely biologic candidates. In conclusion, preliminary results suggest WGS analysis can discover novel loci for complex traits. Work is ongoing to refine annotation for rare variant association tests and perform functional fine-mapping across the genome. We soon will extend our analysis into the next release of WGS data from TOPMed (N∼69,000 individuals). Disclosure J. Wessel: Employee; Spouse/Partner; Eli Lilly and Company. J.A. Brody: None. A. Manning: None.

A subregion-based burden test for simultaneous identification of susceptibility loci and subregions within.

In rare variant association studies, aggregating rare and/or low frequency variants, may increase statistical power for detection of the underlying susceptibility gene or region. However, it is unclear which variants, or class of them, in a gene contribute most to the association. We proposed a subregion-based burden test (REBET) to simultaneously select susceptibility genes and identify important underlying subregions. The subregions are predefined by shared common biologic characteristics, such as the protein domain or functional impact. Based on a subset-based approach considering local correlations between combinations of test statistics of subregions, REBET is able to properly control the type I error rate while adjusting for multiple comparisons in a computationally efficient manner. Simulation studies show that REBET can achieve power competitive to alternative methods when rare variants cluster within subregions. In two case studies, REBET is able to identify known disease susceptibility genes, and more importantly pinpoint the unreported most susceptible subregions, which represent protein domains essential for gene function. R package REBET is available at https://dceg.cancer.gov/tools/analysis/rebet.

Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease

BackgroundProstate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes.MethodsWe sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis ≥60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants.ResultsProtein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects.ConclusionsInherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application.

Associations of single nucleotide polymorphisms with mucinous colorectal cancer: genome-wide common variant and gene-based rare variant analyses

BackgroundColorectal cancer has significant impact on individuals and healthcare systems. Many genes have been identified to influence its pathogenesis. However, the genetic basis of mucinous tumor histology, an aggressive subtype of colorectal cancer, is currently not well-known. This study aimed to identify common and rare genetic variations that are associated with the mucinous tumor phenotype.MethodsGenome-wide single nucleotide polymorphism (SNP) data was investigated in a colorectal cancer patient cohort (n = 505). Association analyses were performed for 729,373 common SNPs and 275,645 rare SNPs. Common SNP association analysis was performed using univariable and multivariable logistic regression under different genetic models. Rare-variant association analysis was performed using a multi-marker test.ResultsNo associations reached the traditional genome-wide significance. However, promising genetic associations were identified. The identified common SNPs significantly improved the discriminatory accuracy of the model for mucinous tumor phenotype. Specifically, the area under the receiver operating characteristic curve increased from 0.703 (95% CI: 0.634–0.773) to 0.916 (95% CI: 0.873–0.960) when considering the most significant SNPs. Additionally, the rare variant analysis identified a number of genetic regions that potentially contain causal rare variants associated with the mucinous tumor phenotype.ConclusionsThis is the first study applying both common and rare variant analyses to identify genetic associations with mucinous tumor phenotype using a genome-wide genotype data. Our results suggested novel associations with mucinous tumors. Once confirmed, these results will not only help us understand the biological basis of mucinous histology, but may also help develop targeted treatment options for mucinous tumors.

Whole Exome Sequencing of Patients from Multicase Families with Systemic Lupus Erythematosus Identifies Multiple Rare Variants

In an effort to identify rare alleles associated with SLE, we have performed whole exome sequencing of the most distantly related affected individuals from two large Icelandic multicase SLE families followed by Ta targeted genotyping of additional relatives. We identified multiple rare likely pathogenic variants in nineteen genes co-segregating with the disease through multiple generations. Gene co-expression and protein-protein interaction analysis identified a network of highly connected genes comprising several loci previously implicated in autoimmune diseases. These genes were significantly enriched for immune system development, lymphocyte activation, DNA repair, and V(D)J gene recombination GO-categories. Furthermore, we found evidence of aggregate association and enrichment of rare variants at the FAM71E1/EMC10 locus in an independent set of 4,254 European SLE-cases and 4,349 controls. Our study presents evidence supporting that multiple rare likely pathogenic variants, in newly identified genes involved in known disease pathogenic pathways, segregate with SLE at the familial and population level.

Interdisciplinary Models for Research and Clinical Endeavors in Genomic Medicine: A Scientific Statement From the American Heart Association.

The completion of the Human Genome Project has unleashed a wealth of human genomics information, but it remains unclear how best to implement this information for the benefit of patients. The standard approach of biomedical research, with researchers pursuing advances in knowledge in the laboratory and, separately, clinicians translating research findings into the clinic as much as decades later, will need to give way to new interdisciplinary models for research in genomic medicine. These models should include scientists and clinicians actively working as teams to study patients and populations recruited in clinical settings and communities to make genomics discoveries-through the combined efforts of data scientists, clinical researchers, epidemiologists, and basic scientists-and to rapidly apply these discoveries in the clinic for the prediction, prevention, diagnosis, prognosis, and treatment of cardiovascular diseases and stroke. The highly publicized US Precision Medicine Initiative, also known as All of Us, is a large-scale program funded by the US National Institutes of Health that will energize these efforts, but several ongoing studies such as the UK Biobank Initiative; the Million Veteran Program; the Electronic Medical Records and Genomics Network; the Kaiser Permanente Research Program on Genes, Environment and Health; and the DiscovEHR collaboration are already providing exemplary models of this kind of interdisciplinary work. In this statement, we outline the opportunities and challenges in broadly implementing new interdisciplinary models in academic medical centers and community settings and bringing the promise of genomics to fruition.

Whole-Exome Sequencing in Age-Related Macular Degeneration Identifies Rare Variants in COL8A1, a Component of Bruch’s Membrane

PurposeGenome-wide association studies and targeted sequencing studies of candidate genes have identified common and rare variants that are associated with age-related macular degeneration (AMD). Whole-exome sequencing (WES) studies allow a more comprehensive analysis of rare coding variants across all genes of the genome and will contribute to a better understanding of the underlying disease mechanisms. To date, the number of WES studies in AMD case-control cohorts remains scarce and sample sizes are limited. To scrutinize the role of rare protein-altering variants in AMD cause, we performed the largest WES study in AMD to date in a large European cohort consisting of 1125 AMD patients and 1361 control participants.DesignGenome-wide case-control association study of WES data.ParticipantsOne thousand one hundred twenty-five AMD patients and 1361 control participants.MethodsA single variant association test of WES data was performed to detect variants that are associated individually with AMD. The cumulative effect of multiple rare variants with 1 gene was analyzed using a gene-based CMC burden test. Immunohistochemistry was performed to determine the localization of the Col8a1 protein in mouse eyes.Main Outcome MeasuresGenetic variants associated with AMD.ResultsWe detected significantly more rare protein-altering variants in the COL8A1 gene in patients (22/2250 alleles [1.0%]) than in control participants (11/2722 alleles [0.4%]; P = 7.07×10–5). The association of rare variants in the COL8A1 gene is independent of the common intergenic variant (rs140647181) near the COL8A1 gene previously associated with AMD. We demonstrated that the Col8a1 protein localizes at Bruch’s membrane.ConclusionsThis study supported a role for protein-altering variants in the COL8A1 gene in AMD pathogenesis. We demonstrated the presence of Col8a1 in Bruch’s membrane, further supporting the role of COL8A1 variants in AMD pathogenesis. Protein-altering variants in COL8A1 may alter the integrity of Bruch’s membrane, contributing to the accumulation of drusen and the development of AMD.

Genetic Variants in CPA6 and PRPF31 Are Associated With Variation in Response to Metformin in Individuals With Type 2 Diabetes.

Metformin is the first-line treatment for type 2 diabetes (T2D). Although widely prescribed, the glucose-lowering mechanism for metformin is incompletely understood. Here, we used a genome-wide association approach in a diverse group of individuals with T2D from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial to identify common and rare variants associated with HbA1c response to metformin treatment and followed up these findings in four replication cohorts. Common variants in PRPF31 and CPA6 were associated with worse and better metformin response, respectively (P < 5 × 10-6), and meta-analysis in independent cohorts displayed similar associations with metformin response (P = 1.2 × 10-8 and P = 0.005, respectively). Previous studies have shown that PRPF31(+/-) knockout mice have increased total body fat (P = 1.78 × 10-6) and increased fasted circulating glucose (P = 5.73 × 10-6). Furthermore, rare variants in STAT3 associated with worse metformin response (q <0.1). STAT3 is a ubiquitously expressed pleiotropic transcriptional activator that participates in the regulation of metabolism and feeding behavior. Here, we provide novel evidence for associations of common and rare variants in PRPF31, CPA6, and STAT3 with metformin response that may provide insight into mechanisms important for metformin efficacy in T2D.

Recessive mutations in VPS13D cause childhood onset movement disorders.

VPS13 protein family members VPS13A through VPS13C have been associated with various recessive movement disorders. We describe the first disease association of rare recessive VPS13D variants including frameshift, missense, and partial duplication mutations with a novel complex, hyperkinetic neurological disorder. The clinical features include developmental delay, a childhood onset movement disorder (chorea, dystonia, or tremor), and progressive spastic ataxia or paraparesis. Characteristic brain magnetic resonance imaging shows basal ganglia or diffuse white matter T2 hyperintensities as seen in Leigh syndrome and choreoacanthocytosis. Muscle biopsy in 1 case showed mitochondrial aggregates and lipidosis, suggesting mitochondrial dysfunction. These findings underline the importance of the VPS13 complex in neurological diseases and a possible role in mitochondrial function. Ann Neurol 2018;83:1089-1095.

F193. DYSREGULATION OF RETINOID SIGNALLING IN SCHIZOPHRENIA OBSERVED IN WHOLE GENOME SEQUENCE ANALYSIS

BackgroundRetinoic acid (RA) is intrinsically linked to neurodevelopment and has been implicated in schizophrenia (SZ). This is supported by preliminary trials of a retinoid receptor agonist, Bexarotene, as an adjuvant and the association of five common variants in proximity to members of this pathway at genome wide significance. In addition to these high frequency variants with small effect size, we suspect that this pathway is also affected by rare variants with much higher impact. We aimed to examine the burden of variants in retinoid loci in schizophrenia along with its potential consequences for clinical practice.MethodsWhole genome sequencing was performed on SZ cases (N=331) and non-psychiatric controls (N=167). Cases were further clustered by cognitive measures to derive the cognitive deficit (CD; N=166) and cognitively spared (CS; N=165) subtypes. Disease and subtype associated genomic variation was then analysed in a panel of 129 genes selected for involvement in RA biology (Molecular Signatures Database). Rare variation was aggregated at the gene level using the optimal unified sequence kernel association test (SKAT-O). Clinical metadata was further examined for each case with a rare putative high impact loss of function variant in a RA panel gene predicted using SnpEff. The rare variant burden on target genes of RA receptor binding in SZ was investigated by logistic regression of variants mapped to consensus 5 base pair spaced direct repeat (DR5) retinoic acid response element (RARE) motifs.ResultsGene level rare variant association uncovered suggestive associations with SZ (P < 0.01) for three retinoid genes – RBP3, ADH1C and RPE65. In addition, a stronger signal was detected overall for CD cases implicating four additional genes including the RA receptors RARB (P = 1.1 x 10–3) and RARG (P = 9.2 x 10–3). SZ patients with a rare high impact genotype predicted in a RA panel gene were more likely to have serious symptomology as defined by a global assessment of functioning (GAF) score below 50, P = 7.1 x 10–3 (Two-Tailed Fisher’s Exact Test). We also found evidence of an increased burden of rare variants within predicted DR5-RARE in SZ (P = 0.017, odds ratio [OR] = 1.094, 95% confidence interval [CI] = 1.023- 1.186), however, there was no significant difference between the cognitive subtypes (CD/CS, P = 0.8, OR = 1.002, 95% CI = 0.961–1.045).DiscussionOur findings suggest that RA mediated control of gene expression is heterogeneously disrupted in SZ by rare variants in DR5-RARE motifs. Strong signals in the context of our sample size further support the possibility of enrichment of rare loci in genes involved with RA biology, particularly in CD cases with impaired cognition. Moreover, we identified a subset of patients with likely high effect size genotypes in the RA pathway. Future work will examine whether these high-risk patients would benefit from retinoid based pharmacological intervention.