Discovery Of Genetic Variants Research Articles

PolarMorphism enables discovery of shared genetic variants across multiple traits from GWAS summary statistics.

MotivationPleiotropic SNPs are associated with multiple traits. Such SNPs can help pinpoint biological processes with an effect on multiple traits or point to a shared etiology between traits. We present PolarMorphism, a new method for the identification of pleiotropic SNPs from genome-wide association studies (GWAS) summary statistics. PolarMorphism can be readily applied to more than two traits or whole trait domains. PolarMorphism makes use of the fact that trait-specific SNP effect sizes can be seen as Cartesian coordinates and can thus be converted to polar coordinates r (distance from the origin) and theta (angle with the Cartesian x-axis, in the case of two traits). r describes the overall effect of a SNP, while theta describes the extent to which a SNP is shared. r and theta are used to determine the significance of SNP sharedness, resulting in a P-value per SNP that can be used for further analysis.ResultsWe apply PolarMorphism to a large collection of publicly available GWAS summary statistics enabling the construction of a pleiotropy network that shows the extent to which traits share SNPs. We show how PolarMorphism can be used to gain insight into relationships between traits and trait domains and contrast it with genetic correlation. Furthermore, pathway analysis of the newly discovered pleiotropic SNPs demonstrates that analysis of more than two traits simultaneously yields more biologically relevant results than the combined results of pairwise analysis of the same traits. Finally, we show that PolarMorphism is more efficient and more powerful than previously published methods.Availability and implementationcode: https://github.com/UMCUGenetics/PolarMorphism, results: 10.5281/zenodo.5844193.Supplementary information Supplementary data are available at Bioinformatics online.

P510. Making the MOSTest of Genetics: The Multivariate Omnibus Statistical Test Boosts Discovery of the Genetic Determinants of the Brain and its Disorders

Regional brain morphology and associated psychiatric traits have complex genetic architectures, which has proven challenging for genome-wide association studies (GWAS). Given high pleiotropy, joint analysis of clinically relevant measures through the novel multivariate omnibus statistical test (MOSTest) enhances discovery of genetic variants with current sample sizes.

Successful storage of Trichomonas gallinae on Whatman FTA cards following culture

Logistical constraints concerning parasite sample storage can hinder progress with the discovery of genetic variation on a global scale. New storage methods are being developed to address this, but require testing in order to understand how widely applicable these methods are. Whatman FTA cards have been tested previously under laboratory conditions for storing low-concentration Trichomonas gallinae isolates with the conclusion that they are not suitable, but have not been tested under field conditions. Here, we conducted a field-test, comparing FTA cards with storage in ethanol for T. gallinae samples collected and cultured from wild Columbiformes in Africa using standard field methods, before transportation to the UK. After 6 months storage, both methods resulted in an overall prevalence of 100% following PCR amplification (n = 59), suggesting that FTA cards are suitable for estimation of T. gallinae prevalence. However, samples stored in ethanol produced more, and longer, sequences than those stored on FTA cards. These data suggest storage in ethanol is preferable for the acquisition of high quality genetic strain data, but that FTA cards can be used successfully to ascertain infection prevalence and identify parasite strains under field conditions.

Modern developments in germline pharmacogenomics for oncology prescribing.

The integration of genomic data into personalized treatment planning has revolutionized oncology care. Despite this, patients with cancer remain vulnerable to high rates of adverse drug events and medication inefficacy, affecting prognosis and quality of life. Pharmacogenomics is a field seeking to identify germline genetic variants that contribute to an individual's unique drug response. Although there is widespread integration of genomic information in oncology, somatic platforms, rather than germline biomarkers, have dominated the attention of cancer providers. Patients with cancer potentially stand to benefit from improved integration of both somatic and germline genomic information, especially because the latter may complement treatment planning by informing toxicity risk for drugs with treatment-limiting tolerabilities and narrow therapeutic indices. Although certain germline pharmacogenes, such as TPMT, UGT1A1, and DPYD, have been recognized for decades, recent attention has illuminated modern potential dosing implications for a whole new set of anticancer agents, including targeted therapies and antibody-drug conjugates, as well as the discovery of additional genetic variants and newly relevant pharmacogenes. Some of this information has risen to the level of directing clinical action, with US Food and Drug Administration label guidance and recommendations by international societies and governing bodies. This review is focused on key new pharmacogenomic evidence and oncology-specific dosing recommendations. Personalized oncology care through integrated pharmacogenomics represents a unique multidisciplinary collaboration between oncologists, laboratory science, bioinformatics, pharmacists, clinical pharmacologists, and genetic counselors, among others. The authors posit that expanded consideration of germline genetic information can further transform the safe and effective practice of oncology in 2022 and beyond.

Insights From Dimensional Phenotypic Definitions of Posttraumatic Stress Disorder and Trauma in Genome-wide Association Studies

Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure InformationBiological PsychiatryVol. 91Issue 7PreviewPosttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Full-Text PDF Open Access

Cramp fasciculation syndrome-associated TRPA1 mutant reveals new gating insights and illuminates roles of C-terminal regions on channel function

TRPA1 is a non-selective homotetrameric cation channel expressed in primary sensory neurons of the pain pathway, where it is activated by diverse chemical irritants. A direct role for TRPA1 in pain sensation has been highlighted by the discovery of genetic variants associated with severe pain disorders. One such heterozygous premature termination codon mutant (R919∗) was identified in a father-son pair with cramp fasciculation syndrome (CFS) and neuronal hyperexcitability-hypersensitivity symptoms potentially caused by aberrant channel activity, though the mechanism of action for this mutant is unknown.

Considering Toxic Chemicals in the Etiology of Autism.

Considering Toxic Chemicals in the Etiology of Autism.

Spacing Constraints of Neighboring Zinc Finger Modules within GATA2

Genomic analyses in clinical and experimental contexts have accelerated discoveries of human genetic variants. While elucidating the consequences of conspicuously loss-of-function variants is highly tractable, decoding the impact of missense or non-coding variants is considerably more challenging. Previously, we described a germline variant in GATA2 in a patient with GATA2-deficiency syndrome, which inserts nine amino acids between the two zinc fingers (9aa-Ins), one of which mediates sequence-specific DNA binding (Cavalcante de Andrade Silva M. et al., Leukemia, 2021). Unlike other GATA2 coding region and enhancer variants identified (Bresnick E.H. et al., Blood Adv., 2020), it was unclear whether the altered zinc finger spacing would be inhibitory, stimulatory or of no consequence. The 9aa-Ins variant was defective in activating several target genes (Hdc, Ear2 and Tpsb2) in a genetic complementation assay with Gata2 -77 enhancer-mutant (-77 -/-) primary hematopoietic progenitor cells. As only several target genes were tested, we used RNA-seq to conduct a genome-wide comparison of the capacity of GATA2 and 9aa-Ins to activate and repress transcription. To elucidate mechanisms, we considered the following models: 1) 9aa-Ins fails to regulate all genes normally controlled by GATA2; 2) 9aa-Ins fails to repress all genes normally controlled by GATA2; 3) 9aa-Ins fails to activate genes normally controlled by GATA2; 4) 9aa-Ins ectopically regulates genes not controlled by GATA2. Using a genetic complementation approach with -77 -/- cells that were immortalized by the Hoxb8 transcription factor (hi-77 -/-) (Wang G.G. et al., Nat. Methods, 2006; Johnson K.D. et al., JEM, 2020), we compared GATA2 and 9aa-Ins activities when expressed at a comparable level. This analysis revealed 2,138 GATA2-regulated, 525 GATA2 and 9aa-Ins-regulated, and 414 ectopically-regulated genes (at least two-fold change, adjusted P-value <0.05). A similar number of genes were GATA2-activated (1,061) and repressed (1,077). Only 144 out of the 1,061 (14%) were 9aa-Ins-activated and 381 out of 1,077 (35%) were 9aa-Ins-repressed, illustrating the severe consequences of this mutation and a greater impact on activation versus repression. Statistical analysis with a range of P-values constraints (0.01 to 0.1) verified that activation by 9aa-Ins was more significantly impaired than repression (86% were no longer activated, and 65% were no longer repressed, P = 5.4 x 10 -6). Gene ontology analysis revealed that the 9aa insertion impaired GATA2-mediated activation of genes related to GPCR signaling and GATA2-mediated repression of genes related to innate immune machinery. The ectopically-regulated genes did not conform to a particular mechanism or pathway.Since it was unclear whether the transcriptional defects of the 9aa-Ins mutant reflect a unique inhibitory activity imparted by the 9aa sequence, we systematically varied the inter-zinc finger spacer length to establish whether any alterations can be tolerated. Using the genetic complementation assay, 2, 4, 6, 8, and 9aa spacer variants were compared with GATA2 for their capacity to regulate GATA2-activated genes (Hdc, Il1rl1, Gata1 and S1pr1) and repressed genes (Irf8, Il6st, Il6ra and Tifab). GATA2-mediated activation was compromised by insertions of two amino acids or more, whereas repression tolerated two and four amino acid insertions; 6, 8 and 9 were more inhibitory. Quantitative analyses revealed that a 6aa insertion reduced activation of the GATA2-activated genes by >50% of the wild type value, whereas the GATA2-repressed genes were still repressed by at least 50% (18% retention of activation and 83% retention of repression, P = 0.001). Thus, zinc finger spacing alterations differentially impacted activation versus repression. These results provide a rigorous foundation for interpreting variants that alter zinc finger spacing without disrupting vital finger residues. In vitro and in vivo functional analyses and molecular modeling are ongoing to further dissect the underlying mechanisms and ascertain the importance of genetic networks and circuits that are sensitive or resistant to human disease variants. DisclosuresNo relevant conflicts of interest to declare.

Heritable variation in locomotion, reward sensitivity and impulsive behaviors in a genetically diverse inbred mouse panel.

Drugs of abuse, including alcohol and stimulants like cocaine, produce effects that are subject to individual variability, and genetic variation accounts for at least a portion of those differences. Notably, research in both animal models and human subjects point toward reward sensitivity and impulsivity as being trait characteristics that predict relatively greater positive subjective responses to stimulant drugs. Here we describe use of the eight collaborative cross (CC) founder strains and 38 (reversal learning) or 10 (all other tests) CC strains to examine the heritability of reward sensitivity and impulsivity traits, as well as genetic correlations between these measures and existing addiction-related phenotypes. Strains were all tested for activity in an open field and reward sensitivity (intake of chocolate BOOST®). Mice were then divided into two counterbalanced groups and underwent reversal learning (impulsive action and waiting impulsivity) or delay discounting (impulsive choice). CC and founder mice show significant heritability for impulsive action, impulsive choice, waiting impulsivity, locomotor activity, and reward sensitivity, with each impulsive phenotype determined to be non-correlating, independent traits. This research was conducted within the broader, inter-laboratory effort of the Center for Systems Neurogenetics of Addiction (CSNA) to characterize CC and DO mice for multiple, cocaine abuse related traits. These data will facilitate the discovery of genetic correlations between predictive traits, which will then guide discovery of genes and genetic variants that contribute to addictive behaviors.

Genetic predictors and pathophysiological features of non-alcoholic fat liver disease

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of liver disease in highly developed countries. The risk of developing NAFLD and associated complications varies greatly among people of different nationalities and is determined by environmental and genetic factors. Genome-wide studies have revealed strong and reproducible associations between gene variations such as PNPLA3, TM6SF2, MBOAT7, GCKR, HSD17B1, and NAFLD. In this article, we consider the influence of genes and environmental factors on the pathophysiological features of NAFLD. The use of a sufficient population sample with the analysis of SNP arrays and the use of sequencing methods (exome and genome as a whole) will lead to the discovery of additional genetic variants, will inevitably improve the understanding of the pathogenesis of NAFLD, and will allow the development of a technology for personalized risk in assessing the disease in a patient. The aim of our study was to study the genetic predictors of NAFLD based on literature data with the interpretation of the studies. There is now strong evidence that specific variants of genetic risk have a large effect on NAFLD, and their effect is comparable to that of major metabolic risk factors such as obesity and type 2 diabetes. The increased risk extends to the onset and progression of the entire spectrum of NAFLD manifestations, including overall mortality due to liver disease. Currently, individual genetic variants do not allow the creation of a personalized risk profile; therefore, the most expedient approach today is the development of polygenic risk assessments. The number of genetic loci associated with the prevalence and outcome of NAFLD remains limited. The use of a sufficient population sample with the analysis of SNP arrays and the use of sequencing methods (exome and genome as a whole) will lead to the discovery of additional genetic variants and will inevitably improve the understanding of the pathogenesis of NAFLD and will allow the development of a technology for personalized risk in the assessment of the disease.

Genome sequencing data analysis for rare disease gene discovery.

Rare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 different disorders, with majority having a genetic origin, and affect roughly 300 million people globally. Most of the patients and their families undergo a long and frustrating diagnostic odyssey. However, advances in the field of genomics have started to facilitate the process of diagnosis, though it is hindered by the difficulty in genome data analysis and interpretation. A major impediment in diagnosis is in the understanding of the diverse approaches, tools and datasets available for variant prioritization, the most important step in the analysis of millions of variants to select a few potential variants. Here we present a review of the latest methodological developments and spectrum of tools available for rare disease genetic variant discovery and recommend appropriate data interpretation methods for variant prioritization. We have categorized the resources based on various steps of the variant interpretation workflow, starting from data processing, variant calling, annotation, filtration and finally prioritization, with a special emphasis on the last two steps. The methods discussed here pertain to elucidating the genetic basis of disease in individual patient cases via trio- or family-based analysis of the genome data. We advocate the use of a combination of tools and datasets and to follow multiple iterative approaches to elucidate the potential causative variant.

Targeted Hybridization Capture of SARS-CoV-2 and Metagenomics Enables Genetic Variant Discovery and Nasal Microbiome Insights.

ABSTRACTThe emergence of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic variants that may alter viral fitness highlights the urgency of widespread next-generation sequencing (NGS) surveillance. To profile genetic variants of the entire SARS-CoV-2 genome, we developed and clinically validated a hybridization capture SARS-CoV-2 NGS assay, integrating novel methods for panel design using double-stranded DNA (dsDNA) biotin-labeled probes, and built accompanying software. This test is the first hybrid capture-based NGS assay given Food and Drug Administration (FDA) emergency use authorization for detection of the SARS-CoV-2 virus. The positive and negative percent agreement (PPA and NPA, respectively) were defined in comparison to the results for an orthogonal real-time reverse transcription polymerase chain reaction (RT-PCR) assay (PPA and NPA, 96.7 and 100%, respectively). The limit of detection was established to be 800 copies/ml with an average fold enrichment of 46,791. Furthermore, utilizing the research-use-only analysis to profile the variants, we identified 55 novel mutations, including 11 in the functionally important spike protein. Finally, we profiled the full nasopharyngeal microbiome using metagenomics and found overrepresentation of 7 taxa and evidence of macrolide resistance in SARS-CoV-2-positive patients. This hybrid capture NGS assay, coupled with optimized software, is a powerful approach to detect and comprehensively map SARS-CoV-2 genetic variants for tracking viral evolution and guiding vaccine updates.IMPORTANCE This is the first FDA emergency-use-authorized hybridization capture-based next-generation sequencing (NGS) assay to detect the SARS-CoV-2 genome. Viral metagenomics and the novel hybrid capture NGS-based assay, along with its research-use-only analysis, can provide important genetic insights into SARS-CoV-2 and other emerging pathogens and improve surveillance and early detection, potentially preventing or mitigating new outbreaks. Better understanding of the continuously evolving SARS-CoV-2 viral genome and the impact of genetic variants may provide individual risk stratification, precision therapeutic options, improved molecular diagnostics, and population-based therapeutic solutions.

Genetic Diagnosis in Hereditary Hemochromatosis: Discovering and Understanding the Biological Relevance of Variants.

Hereditary hemochromatosis (HH) is a genetic disease, leading to iron accumulation and possible organ damage. Patients are usually homozygous for p. Cys282Tyr in the homeostatic iron regulator gene but may have mutations in other genes involved in the regulation of iron. Next-generation sequencing is increasingly being utilized for the diagnosis of patients, leading to the discovery of novel genetic variants. The clinical significance of these variants is often unknown. Determining the pathogenicity of such variants of unknown significance is important for diagnostics and genetic counseling. Predictions can be made using in silico computational tools and population data, but additional evidence is required for a conclusive pathogenicity classification. Genetic disease models, such as in vitro models using cellular overexpression, induced pluripotent stem cells or organoids, and in vivo models using mice or zebrafish all have their own challenges and opportunities when used to model HH and other iron disorders. Recent developments in gene-editing technologies are transforming the field of genetic disease modeling. In summary, this review addresses methods and developments regarding the discovery and classification of genetic variants, from in silico tools to in vitro and in vivo models, and presents them in the context of HH. It also explores recent gene-editing developments and how they can be applied to the discussed models of genetic disease.

A Review of Completed and Ongoing Complement Inhibitor Trials for Geographic Atrophy Secondary to Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is a leading cause of irreversible blindness among older adults in the Western world. While therapies exist for patients with exudative AMD, there are currently no approved therapies for non-exudative AMD and its advanced form of geographic atrophy (GA). The discovery of genetic variants in complement protein loci with increased susceptibility to AMD has led to the investigation of the role of complement inhibition in AMD with a focus on GA. Here, we review completed and ongoing clinical trials evaluating the safety and efficacy of these studies. Overall, complement inhibition in GA has yielded mixed results. The inhibition of complement factor D has failed pivotal phase 3 trials. Studies of C3 and C5 inhibition meeting their primary endpoint are limited by high rates of discontinuation and withdrawal in the treatment arm and higher risks of conversion to exudative AMD. Studies evaluating other complement members (CFB, CFH, CFI and inhibitors of membrane attack complex—CD59) are ongoing and could offer other viable strategies.

Downregulation by CNNM2 of ATP5MD expression in the 10q24.32 schizophrenia-associated locus involved in impaired ATP production and neurodevelopment

Genome-wide association studies (GWAS) have accelerated the discovery of numerous genetic variants associated with schizophrenia. However, most risk variants show a small effect size (odds ratio (OR) <1.2), suggesting that more functional risk variants remain to be identified. Here, we employed region-based multi-marker analysis of genomic annotation (MAGMA) to identify additional risk loci containing variants with large OR value from Psychiatry Genomics Consortium (PGC2) schizophrenia GWAS data and then employed summary-data-based mendelian randomization (SMR) to prioritize schizophrenia susceptibility genes. The top-ranked susceptibility gene ATP5MD, encoding an ATP synthase membrane subunit, is observed to be downregulated in schizophrenia by the risk allele of CNNM2-rs1926032 in the schizophrenia-associated 10q24.32 locus. The Atp5md knockout (KO) in mice was associated with abnormal startle reflex and gait, and ATP5MD knockdown (KD) in human induced pluripotent stem cell-derived neurons disrupted the neural development and mitochondrial respiration and ATP production. Moreover, CNNM2-rs1926032 KO could induce downregulation of ATP5MD expression and disruptions of mitochondrial respiration and ATP production. This study constitutes an important mechanistic component that links schizophrenia-associated CNNM2 regions to disruption in energy adenosine system modulation and neuronal function by long-distance chromatin domain downregulation of ATP5MD. This pathogenic mechanism provides therapeutic implications for schizophrenia.

Making the MOSTest of Imaging Genetics

Regional brain morphology has a complex genetic architecture, consisting of many common polymorphisms with small individual effects, which has proven challenging for genome-wide association studies (GWAS), despite its high heritability. Given the distributed nature of genetic signal across brain regions, joint analysis of regional morphology measures in a multivariate statistical framework provides a way to enhance discovery of genetic variants with current sample sizes.

Efficiency of whole-exome sequencing in old world and new world primates using human capture reagents.

Whole-exome sequencing (WES) can expedite research on genetic variation in non-human primate (NHP) models of human diseases. However, NHP-specific reagents for exome capture are not available. This study reports the use of human-specific capture reagents in WES for olive baboons, marmosets, and vervet monkeys. Exome capture was carried out using the SureSelect Human All Exon V6 panel from Agilent Technologies, followed by high-throughput sequencing. Capture of protein-coding genes and detection of single nucleotide variants were evaluated. Exome capture and sequencing results showed that more than 97% of old world and 93% of new world monkey protein coding genes were detected. Single nucleotide variants were detected across the genomes and missense variants were found in genes associated with human diseases. A cost-effective approach based on commercial, human-specific reagents can be used to perform WES for the discovery of genetic variants in these NHP species.

Exome-wide age-of-onset analysis reveals exonic variants in ERN1 and SPPL2C associated with Alzheimer\u2019s disease

Despite recent discoveries in genome-wide association studies (GWAS) of genomic variants associated with Alzheimer’s disease (AD), its underlying biological mechanisms are still elusive. The discovery of novel AD-associated genetic variants, particularly in coding regions and from APOEε4 non-carriers, is critical for understanding the pathology of AD. In this study, we carried out an exome-wide association analysis of age-of-onset of AD with ~20,000 subjects and placed more emphasis on APOEε4 non-carriers. Using Cox mixed-effects models, we find that age-of-onset shows a stronger genetic signal than AD case-control status, capturing many known variants with stronger significance, and also revealing new variants. We identified two novel variants, rs56201815, a rare synonymous variant in ERN1, and rs12373123, a common missense variant in SPPL2C in the MAPT region in APOEε4 non-carriers. Besides, a rare missense variant rs144292455 in TACR3 showed the consistent direction of effect sizes across all studies with a suggestive significant level. In an attempt to unravel their regulatory and biological functions, we found that the minor allele of rs56201815 was associated with lower average FDG uptake across five brain regions in ADNI. Our eQTL analyses based on 6198 gene expression samples from ROSMAP and GTEx revealed that the minor allele of rs56201815 was potentially associated with elevated expression of ERN1, a key gene triggering unfolded protein response (UPR), in multiple brain regions, including the posterior cingulate cortex and nucleus accumbens. Our cell-type-specific eQTL analysis using ~80,000 single nuclei in the prefrontal cortex revealed that the protective minor allele of rs12373123 significantly increased the expression of GRN in microglia, and was associated with MAPT expression in astrocytes. These findings provide novel evidence supporting the hypothesis of the potential involvement of the UPR to ER stress in the pathological pathway of AD, and also give more insights into underlying regulatory mechanisms behind the pleiotropic effects of rs12373123 in multiple degenerative diseases including AD and Parkinson’s disease.

Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome

Alternative splicing (AS) is a fundamental step in eukaryotic mRNA biogenesis. Here, we develop an efficient and reproducible pipeline for the discovery of genetic variants that affect AS (splicing QTLs, sQTLs). We use it to analyze the GTEx dataset, generating a comprehensive catalog of sQTLs in the human genome. Downstream analysis of this catalog provides insight into the mechanisms underlying splicing regulation. We report that a core set of sQTLs is shared across multiple tissues. sQTLs often target the global splicing pattern of genes, rather than individual splicing events. Many also affect the expression of the same or other genes, uncovering regulatory loci that act through different mechanisms. sQTLs tend to be located in post-transcriptionally spliced introns, which would function as hotspots for splicing regulation. While many variants affect splicing patterns by altering the sequence of splice sites, many more modify the binding sites of RNA-binding proteins. Genetic variants affecting splicing can have a stronger phenotypic impact than those affecting gene expression.

Detecting rare haplotype association with two correlated phenotypes of binary and continuous types.

Multiple correlated traits/phenotypes are often collected in genetic association studies and they may share a common genetic mechanism. Joint analysis of correlated phenotypes has well-known advantages over one-at-a-time analysis including gain in power and better understanding of genetic etiology. However, when the phenotypes are of discordant types such as binary and continuous, the joint modeling is more challenging. Another research area of current interest is discovery of rare genetic variants. Currently there is no method available for detecting association of rare (or common) haplotypes with multiple discordant phenotypes jointly. Our goal is to fill this gap specifically for two discordant phenotypes. We consider a rare haplotype association method for a binary phenotype, logistic Bayesian LASSO (univariate LBL) and its extension for two correlated binary phenotypes (bivariate LBL-2B). Under this framework, we propose a haplotype association test with binary and continuous phenotypes jointly (bivariate LBL-BC). Specifically, we use a latent variable to induce correlation between the two phenotypes. We carry out extensive simulations to investigate bivariate LBL-BC and compare it with univariate LBL and bivariate LBL-2B. In most settings, bivariate LBL-BC performs the best. In only two situations, bivariate LBL-BC has similar performance-when the two phenotypes are (1) weakly or not correlated and the target haplotype affects the binary phenotype only and (2) strongly positively correlated and the target haplotype affects both phenotypes in positive direction. Finally, we apply the method to a data set on lung cancer and nicotine dependence and detect several haplotypes including a rare one.