Aneuploidy effects on human gene expression across three cell types.

Aneuploidy syndromes impact multiple organ systems but understanding of tissue-specific aneuploidy effects remains limited-especially for the comparison between peripheral tissues and relatively inaccessible tissues like brain. Here, we address this gap in knowledge by studying the transcriptomic effects of chromosome X, Y, and 21 aneuploidies in lymphoblastoid cell lines, fibroblasts and iPSC-derived neuronal cells (LCLs, FCL, and iNs, respectively). We root our analyses in sex chromosome aneuploidies, which offer a uniquely wide karyotype range for dosage effect analysis. We first harness a large LCL RNA-seq dataset from 197 individuals with one of 6 sex chromosome dosages (SCDs: XX, XXX, XY, XXY, XYY, and XXYY) to i) validate theoretical models of SCD sensitivity and ii) define an expanded set of 41 genes that show obligate dosage sensitivity to SCD and are all in cis (i.e., reside on the X or Y chromosome). We then use multiple complementary analyses to show that cis effects of SCD in LCLs are preserved in both FCLs (n = 32) and iNs (n = 24), whereas trans effects (i.e., those on autosomal gene expression) are mostly not preserved. Analysis of additional datasets confirms that the greater cross-cell type reproducibility of cis vs. trans effects is also seen in trisomy 21 cell lines. These findings i) expand our understanding of X, Y, and 21 chromosome dosage effects on human gene expression and ii) suggest that LCLs may provide a good model system for understanding cis effects of aneuploidy in harder-to-access cell types.

Cellular Diversity in Human Subgenual Anterior Cingulate and Dorsolateral Prefrontal Cortex by Single-Nucleus RNA-Sequencing.

Regional cellular heterogeneity is a fundamental feature of the human neocortex; however, details of this heterogeneity are still undefined. We used single-nucleus RNA-sequencing to examine cell-specific transcriptional features in the dorsolateral PFC (DLPFC) and the subgenual anterior cingulate cortex (sgACC), regions implicated in major psychiatric disorders. Droplet-based nuclei-capture and library preparation were performed on replicate samples from 8 male donors without history of psychiatric or neurologic disorder. Unsupervised clustering identified major neural cell classes. Subsequent iterative clustering of neurons further revealed 20 excitatory and 22 inhibitory subclasses. Inhibitory cells were consistently more abundant in the sgACC and excitatory neuron subclusters exhibited considerable variability across brain regions. Excitatory cell subclasses also exhibited greater within-class transcriptional differences between the two regions. We used these molecular definitions to determine which cell classes might be enriched in loci carrying a genetic signal in genome-wide association studies or for differentially expressed genes in mental illness. We found that the heritable signals of psychiatric disorders were enriched in neurons and that, while the gene expression changes detected in bulk-RNA-sequencing studies were dominated by glial cells, some alterations could be identified in specific classes of excitatory and inhibitory neurons. Intriguingly, only two excitatory cell classes exhibited concomitant region-specific enrichment for both genome-wide association study loci and transcriptional dysregulation. In sum, by detailing the molecular and cellular diversity of the DLPFC and sgACC, we were able to generate hypotheses on regional and cell-specific dysfunctions that may contribute to the development of mental illness.SIGNIFICANCE STATEMENT Dysfunction of the subgenual anterior cingulate cortex has been implicated in mood disorders, particularly major depressive disorder, and the dorsolateral PFC, a subsection of the PFC involved in executive functioning, has been implicated in schizophrenia. Understanding the cellular composition of these regions is critical to elucidating the neurobiology underlying psychiatric and neurologic disorders. We studied cell type diversity of the subgenual anterior cingulate cortex and dorsolateral PFC of humans with no neuropsychiatric illness using a clustering analysis of single-nuclei RNA-sequencing data. Defining the transcriptomic profile of cellular subpopulations in these cortical regions is a first step to demystifying the cellular and molecular pathways involved in psychiatric disorders.

Genome-wide significant risk loci for mood disorders in the Old Order Amish founder population.

Genome-wide association studies (GWAS) of mood disorders in large case-control cohorts have identified numerous risk loci, yet pathophysiological mechanisms remain elusive, primarily due to the very small effects of common variants. We sought to discover risk variants with larger effects by conducting a genome-wide association study of mood disorders in a founder population, the Old Order Amish (OOA, n = 1,672). Our analysis revealed four genome-wide significant risk loci, all of which were associated with >2-fold relative risk. Quantitative behavioral and neurocognitive assessments (n = 314) revealed effects of risk variants on sub-clinical depressive symptoms and information processing speed. Network analysis suggested that OOA-specific risk loci harbor novel risk-associated genes that interact with known neuropsychiatry-associated genes via gene interaction networks. Annotation of the variants at these risk loci revealed population-enriched, non-synonymous variants in two genes encoding neurodevelopmental transcription factors, CUX1 and CNOT1. Our findings provide insight into the genetic architecture of mood disorders and a substrate for mechanistic and clinical studies.

Rare variants implicate NMDA receptor signaling and cerebellar gene networks in risk for bipolar disorder.

Bipolar disorder is an often-severe mental health condition characterized by alternation between extreme mood states of mania and depression. Despite strong heritability and the recent identification of 64 common variant risk loci of small effect, pathophysiological mechanisms remain unknown. Here, we analyzed genome sequences from 41 multiply-affected pedigrees and identified variants in 741 genes with nominally significant linkage or association with bipolar disorder. These 741 genes overlapped known risk genes for neurodevelopmental disorders and clustered within gene networks enriched for synaptic and nuclear functions. The top variant in this analysis - prioritized by statistical association, predicted deleteriousness, and network centrality - was a missense variant in the gene encoding D-amino acid oxidase (DAOG131V). Heterologous expression of DAOG131V in human cells resulted in decreased DAO protein abundance and enzymatic activity. In a knock-in mouse model of DAOG131, DaoG130V/+, we similarly found decreased DAO protein abundance in hindbrain regions, as well as enhanced stress susceptibility and blunted behavioral responses to pharmacological inhibition of N-methyl-D-aspartate receptors (NMDARs). RNA sequencing of cerebellar tissue revealed that DaoG130V resulted in decreased expression of two gene networks that are enriched for synaptic functions and for genes expressed, respectively, in Purkinje neurons or granule neurons. These gene networks were also down-regulated in the cerebellum of patients with bipolar disorder compared to healthy controls and were enriched for additional rare variants associated with bipolar disorder risk. These findings implicate dysregulation of NMDAR signaling and of gene expression in cerebellar neurons in bipolar disorder pathophysiology and provide insight into its genetic architecture.

Genome-wide association study of panic disorder reveals genetic overlap with neuroticism and depression.

Panic disorder (PD) has a lifetime prevalence of 2-4% and heritability estimates of 40%. The contributory genetic variants remain largely unknown, with few and inconsistent loci having been reported. The present report describes the largest genome-wide association study (GWAS) of PD to date comprising genome-wide genotype data of 2248 clinically well-characterized PD patients and 7992 ethnically matched controls. The samples originated from four European countries (Denmark, Estonia, Germany, and Sweden). Standard GWAS quality control procedures were conducted on each individual dataset, and imputation was performed using the 1000 Genomes Project reference panel. A meta-analysis was then performed using the Ricopili pipeline. No genome-wide significant locus was identified. Leave-one-out analyses generated highly significant polygenic risk scores (PRS) (explained variance of up to 2.6%). Linkage disequilibrium (LD) score regression analysis of the GWAS data showed that the estimated heritability for PD was 28.0-34.2%. After correction for multiple testing, a significant genetic correlation was found between PD and major depressive disorder, depressive symptoms, and neuroticism. A total of 255 single-nucleotide polymorphisms (SNPs) with p < 1 × 10-4 were followed up in an independent sample of 2408 PD patients and 228,470 controls from Denmark, Iceland and the Netherlands. In the combined analysis, SNP rs144783209 showed the strongest association with PD (pcomb = 3.10 × 10-7). Sign tests revealed a significant enrichment of SNPs with a discovery p-value of <0.0001 in the combined follow up cohort (p = 0.048). The present integrative analysis represents a major step towards the elucidation of the genetic susceptibility to PD.

Evaluation of Recipients of Positive and Negative Secondary Findings Evaluations in a Hybrid CLIA-Research Sequencing Pilot.

While consensus regarding the return of secondary genomic findings in the clinical setting has been reached, debate about such findings in the research setting remains. We developed a hybrid, research-clinical translational genomics process for research exome data coupled with a CLIA-validated secondary findings analysis. Eleven intramural investigators from ten institutes at the National Institutes of Health piloted this process. Nearly 1,200 individuals were sequenced and 14 secondary findings were identified in 18 participants. Positive secondary findings were returned by a genetic counselor following a standardized protocol, including referrals for specialty follow-up care for the secondary finding local to the participants. Interviews were undertaken with 13 participants 4 months after receipt of a positive report. These participants reported minimal psychologic distress within a process to assimilate their results. Of the 13, 9 reported accessing the recommended health care services. A sample of 107 participants who received a negative findings report were surveyed 4 months after receiving it. They demonstrated good understanding of the negative secondary findings result and most expressed reassurance (64%) from that report. However, a notable minority (up to 17%) expressed confusion regarding the distinction of primary from secondary findings. This pilot shows it is feasible to couple CLIA-compliant secondary findings to research sequencing with minimal harms. Participants managed the surprise of a secondary finding with most following recommended follow up, yet some with negative findings conflated secondary and primary findings. Additional work is needed to understand barriers to follow-up care and help participants distinguish secondary from primary findings.

The genetics of bipolar disorder.

Bipolar disorder (BD) is one of the most heritable mental illnesses, but the elucidation of its genetic basis has proven to be a very challenging endeavor. Genome-Wide Association Studies (GWAS) have transformed our understanding of BD, providing the first reproducible evidence of specific genetic markers and a highly polygenic architecture that overlaps with that of schizophrenia, major depression, and other disorders. Individual GWAS markers appear to confer little risk, but common variants together account for about 25% of the heritability of BD. A few higher-risk associations have also been identified, such as a rare copy number variant on chromosome 16p11.2. Large scale next-generation sequencing studies are actively searching for other alleles that confer substantial risk. As our understanding of the genetics of BD improves, there is growing optimism that some clear biological pathways will emerge, providing a basis for future studies aimed at molecular diagnosis and novel therapeutics.

Review and Consensus on Pharmacogenomic Testing in Psychiatry.

The implementation of pharmacogenomic (PGx) testing in psychiatry remains modest, in part due to divergent perceptions of the quality and completeness of the evidence base and diverse perspectives on the clinical utility of PGx testing among psychiatrists and other healthcare providers. Recognizing the current lack of consensus within the field, the International Society of Psychiatric Genetics assembled a group of experts to conduct a narrative synthesis of the PGx literature, prescribing guidelines, and product labels related to psychotropic medications as well as the key considerations and limitations related to the use of PGx testing in psychiatry. The group concluded that to inform medication selection and dosing of several commonly-used antidepressant and antipsychotic medications, current published evidence, prescribing guidelines, and product labels support the use of PGx testing for 2 cytochrome P450 genes (CYP2D6, CYP2C19). In addition, the evidence supports testing for human leukocyte antigen genes when using the mood stabilizers carbamazepine (HLA-A and HLA-B), oxcarbazepine (HLA-B), and phenytoin (CYP2C9, HLA-B). For valproate, screening for variants in certain genes (POLG, OTC, CSP1) is recommended when a mitochondrial disorder or a urea cycle disorder is suspected. Although barriers to implementing PGx testing remain to be fully resolved, the current trajectory of discovery and innovation in the field suggests these barriers will be overcome and testing will become an important tool in psychiatry.

Genetic versus stress and mood determinants of sleep in the Amish.

Sleep is essential to the human brain and is regulated by genetics with many features conserved across species. Sleep is also influenced by health and environmental factors; identifying replicable genetic variants contributing to sleep may require accounting for these factors. We examined how stress and mood disorder contribute to sleep and impact its heritability. Our sample included 326 Amish/Mennonite individuals with a lifestyle with limited technological interferences with sleep. Sleep measures included Pittsburgh Sleep Quality Index (PSQI), bedtime, wake time, and time to sleep onset. Current stress level, cumulative life stressors, and mood disorder were also evaluated. We estimated the heritability of sleep features and examined the impact of current stress, lifetime stress, mood diagnosis on sleep quality. The results showed current stress, lifetime stress, and mood disorder were independently associated with PSQI score (p < .05). Heritability of PSQI was low (0-0.23) before and after accounting for stress and mood. Bedtime, wake time, and minutes to sleep time did show significant heritability at 0.44, 0.42, and 0.29. However, after adjusting for shared environment, only heritability of wake time remained significant. Sleep is affected by environmental stress and mental health factors even in a society with limited technological interference with sleep. Wake time may be a more biological marker of sleep as compared to the evening measures which are more influenced by other household members. Accounting for nongenetic and partially genetic determinants of sleep particularly stress and mood disorder is likely important for improving the precision of genetic studies of sleep.

Linear mixed models for association analysis of quantitative traits with next-generation sequencing data.

We develop linear mixed models (LMMs) and functional linear mixed models (FLMMs) for gene-based tests of association between a quantitative trait and genetic variants on pedigrees. The effects of a major gene are modeled as a fixed effect, the contributions of polygenes are modeled as a random effect, and the correlations of pedigree members are modeled via inbreeding/kinship coefficients. F -statistics and χ 2 likelihood ratio test (LRT) statistics based on the LMMs and FLMMs are constructed to test for association. We show empirically that the F -distributed statistics provide a good control of the type I error rate. The F -test statistics of the LMMs have similar or higher power than the FLMMs, kernel-based famSKAT (family-based sequence kernel association test), and burden test famBT (family-based burden test). The F -statistics of the FLMMs perform well when analyzing a combination of rare and common variants. For small samples, the LRT statistics of the FLMMs control the type I error rate well at the nominal levels α = 0.01 and 0.05 . For moderate/large samples, the LRT statistics of the FLMMs control the type I error rates well. The LRT statistics of the LMMs can lead to inflated type I error rates. The proposed models are useful in whole genome and whole exome association studies of complex traits.

Sodium valproate rescues expression of TRANK1 in iPSC-derived neural cells that carry a genetic variant associated with serious mental illness.

Biological characterization of genetic variants identified in genome-wide association studies (GWAS) remains a substantial challenge. Here we used human-induced pluripotent stem cells (iPSC) and their neural derivatives to characterize common variants on chromosome 3p22 that have been associated by GWAS with major mental illnesses. IPSC-derived neural progenitor cells carrying the risk allele of the single nucleotide polymorphism (SNP), rs9834970, displayed lower baseline TRANK1 expression that was rescued by chronic treatment with therapeutic dosages of valproic acid (VPA). VPA had the greatest effects on TRANK1 expression in iPSC, NPC, and astrocytes. Although rs9834970 has no known function, we demonstrated that a nearby SNP, rs906482, strongly affects binding by the transcription factor, CTCF, and that the high-affinity allele usually occurs on haplotypes carrying the rs9834970 risk allele. Decreased expression of TRANK1 perturbed expression of many genes involved in neural development and differentiation. These findings have important implications for the pathophysiology of major mental illnesses and the development of novel therapeutics.

From genetics to biology: advancing mental health research in the Genomics ERA.

The Genomics Workgroup of the National Advisory Mental Health Council (NAMHC) recently issued a set of recommendations for advancing the NIMH psychiatric genetics research program and prioritizing subsequent follow-up studies. The report emphasized the primacy of rigorous statistical support from properly designed, well-powered studies for pursuing genetic variants robustly associated with disease. Here we discuss the major points NIMH program staff consider when assessing research applications based on common and rare variants, as well as genetic syndromes, associated with psychiatric disorders. These are broad guiding principles for investigators to consider prior to submission of their applications. NIMH staff weigh these points in the context of reviewer comments, the existing literature, and current investments in related projects. Following the recommendations of the NAMHC, statistical strength and robustness of the underlying genetic discovery weighs heavily in our funding considerations as does the suitability of the proposed experimental approach. We specifically address our evaluation of applications motivated in whole, or in part, by an association between human DNA sequence variation and a disease or trait relevant to the mission of the NIMH.

Rediscovering the value of families for psychiatric genetics research.

As it is likely that both common and rare genetic variation are important for complex disease risk, studies that examine the full range of the allelic frequency distribution should be utilized to dissect the genetic influences on mental illness. The rate limiting factor for inferring an association between a variant and a phenotype is inevitably the total number of copies of the minor allele captured in the studied sample. For rare variation, with minor allele frequencies of 0.5% or less, very large samples of unrelated individuals are necessary to unambiguously associate a locus with an illness. Unfortunately, such large samples are often cost prohibitive. However, by using alternative analytic strategies and studying related individuals, particularly those from large multiplex families, it is possible to reduce the required sample size while maintaining statistical power. We contend that using whole genome sequence (WGS) in extended pedigrees provides a cost-effective strategy for psychiatric gene mapping that complements common variant approaches and WGS in unrelated individuals. This was our impetus for forming the "Pedigree-Based Whole Genome Sequencing of Affective and Psychotic Disorders" consortium. In this review, we provide a rationale for the use of WGS with pedigrees in modern psychiatric genetics research. We begin with a focused review of the current literature, followed by a short history of family-based research in psychiatry. Next, we describe several advantages of pedigrees for WGS research, including power estimates, methods for studying the environment, and endophenotypes. We conclude with a brief description of our consortium and its goals.

Rare variants in neuronal excitability genes influence risk for bipolar disorder.

We sequenced the genomes of 200 individuals from 41 families multiply affected with bipolar disorder (BD) to identify contributions of rare variants to genetic risk. We initially focused on 3,087 candidate genes with known synaptic functions or prior evidence from genome-wide association studies. BD pedigrees had an increased burden of rare variants in genes encoding neuronal ion channels, including subunits of GABAA receptors and voltage-gated calcium channels. Four uncommon coding and regulatory variants also showed significant association, including a missense variant in GABRA6. Targeted sequencing of 26 of these candidate genes in an additional 3,014 cases and 1,717 controls confirmed rare variant associations in ANK3, CACNA1B, CACNA1C, CACNA1D, CACNG2, CAMK2A, and NGF. Variants in promoters and 5' and 3' UTRs contributed more strongly than coding variants to risk for BD, both in pedigrees and in the case-control cohort. The genes and pathways identified in this study regulate diverse aspects of neuronal excitability. We conclude that rare variants in neuronal excitability genes contribute to risk for BD.

Convergent analysis of genome-wide genotyping and transcriptomic data suggests association of zinc finger genes with lithium response in bipolar disorder.

Lithium is the mainstay treatment in bipolar disorder (BD) for its effectiveness in the acute phases of illness and in prevention of recurrences. Lithium's mechanism of action is complex, and while it modulates the function of hundreds of molecular targets, most of these effects could be unspecific and not relevant for its clinical efficacy. In this study, we applied an integrated analytical approach using genome-wide expression and genotyping data from BD patients to identify lithium-responsive genes that may serve as biomarkers of its efficacy. To this purpose, we tested the effect of treatment with lithium chloride 1 mM on the transcriptome of lymphoblasts from 10 lithium responders (LR) and 10 nonresponders (NR) patients and identified genes significantly influenced by the treatment exclusively in LR. These findings were integrated with gene-based analysis on genome-wide genotyping data from an extended sample of 205 BD patients characterized for lithium response. The expression of 29 genes was significantly changed by lithium exclusively in LR. Gene-based analysis showed that two of these genes, zinc finger protein 429 (ZNF429) and zinc finger protein 493 (ZNF493), were also significantly associated with lithium response. Validation with quantitative real-time polymerase chain reaction confirmed the lithium-induced downregulation of ZNF493 in LR (p = .036). Using convergent analyses of genome-wide expression and genotyping data, we identified ZNF493 as a potential lithium-responsive target that may be involved in modulating lithium efficacy in BD. To our knowledge, this is the first evidence supporting the involvement of zinc finger proteins in lithium response.

Amish revisited: next-generation sequencing studies of psychiatric disorders among the Plain people.

The rapid development of next-generation sequencing (NGS) technology has led to renewed interest in the potential contribution of rarer forms of genetic variation to complex non-mendelian phenotypes such as psychiatric illnesses. Although challenging, family-based studies offer some advantages, especially in communities with large families and a limited number of founders. Here we revisit family-based studies of mental illnesses in traditional Amish and Mennonite communities--known collectively as the Plain people. We discuss the new opportunities for NGS in these populations, with particular emphasis on investigating psychiatric disorders. We also address some of the challenges facing NGS-based studies of complex phenotypes in founder populations.

Finding Rare, Disease-Associated Variants in Isolated Groups: Potential Advantages of Mennonite Populations.

Large-scale genotyping and next-generation sequencing techniques have allowed great advances in the field of molecular genetics. Numerous common variants of low impact have been associated with many complex human traits and diseases, such as bipolar disorder and schizophrenia. Although they may exert a greater impact on risk, few rare disease variants have been found, owing to the greatly increased sample sizes that are typically necessary to demonstrate association with rarer variants. One alternative strategy is to study isolated populations, where historical bottlenecks reduce genetic diversity and some otherwise rare variants may drift to higher frequencies. Here we describe the Mennonite population settlements, considering their history of multiple bottlenecks followed by demographic expansion and a currently widespread geographical distribution. We argue that Mennonite populations are valuable partners for studies seeking genetic variants that exert a high impact on risk for a variety of common disorders, including mental illnesses.

In vivo radioligand binding to translocator protein correlates with severity of Alzheimer's disease.

Neuroinflammation is a pathological hallmark of Alzheimer's disease, but its role in cognitive impairment and its course of development during the disease are largely unknown. To address these unknowns, we used positron emission tomography with (11)C-PBR28 to measure translocator protein 18 kDa (TSPO), a putative biomarker for inflammation. Patients with Alzheimer's disease, patients with mild cognitive impairment and older control subjects were also scanned with (11)C-Pittsburgh Compound B to measure amyloid burden. Twenty-nine amyloid-positive patients (19 Alzheimer's, 10 mild cognitive impairment) and 13 amyloid-negative control subjects were studied. The primary goal of this study was to determine whether TSPO binding is elevated in patients with Alzheimer's disease, and the secondary goal was to determine whether TSPO binding correlates with neuropsychological measures, grey matter volume, (11)C-Pittsburgh Compound B binding, or age of onset. Patients with Alzheimer's disease, but not those with mild cognitive impairment, had greater (11)C-PBR28 binding in cortical brain regions than controls. The largest differences were seen in the parietal and temporal cortices, with no difference in subcortical regions or cerebellum. (11)C-PBR28 binding inversely correlated with performance on Folstein Mini-Mental State Examination, Clinical Dementia Rating Scale Sum of Boxes, Logical Memory Immediate (Wechsler Memory Scale Third Edition), Trail Making part B and Block Design (Wechsler Adult Intelligence Scale Third Edition) tasks, with the largest correlations observed in the inferior parietal lobule. (11)C-PBR28 binding also inversely correlated with grey matter volume. Early-onset (<65 years) patients had greater (11)C-PBR28 binding than late-onset patients, and in parietal cortex and striatum (11)C-PBR28 binding correlated with lower age of onset. Partial volume corrected and uncorrected results were generally in agreement; however, the correlation between (11)C-PBR28 and (11)C-Pittsburgh Compound B binding was seen only after partial volume correction. The results suggest that neuroinflammation, indicated by increased (11)C-PBR28 binding to TSPO, occurs after conversion of mild cognitive impairment to Alzheimer's disease and worsens with disease progression. Greater inflammation may contribute to the precipitous disease course typically seen in early-onset patients. (11)C-PBR28 may be useful in longitudinal studies to mark the conversion from mild cognitive impairment or to assess response to experimental treatments of Alzheimer's disease.

Genome-wide association of bipolar disorder suggests an enrichment of replicable associations in regions near genes.

Although a highly heritable and disabling disease, bipolar disorder's (BD) genetic variants have been challenging to identify. We present new genotype data for 1,190 cases and 401 controls and perform a genome-wide association study including additional samples for a total of 2,191 cases and 1,434 controls. We do not detect genome-wide significant associations for individual loci; however, across all SNPs, we show an association between the power to detect effects calculated from a previous genome-wide association study and evidence for replication (P = 1.5×10(-7)). To demonstrate that this result is not likely to be a false positive, we analyze replication rates in a large meta-analysis of height and show that, in a large enough study, associations replicate as a function of power, approaching a linear relationship. Within BD, SNPs near exons exhibit a greater probability of replication, supporting an enrichment of reproducible associations near functional regions of genes. These results indicate that there is likely common genetic variation associated with BD near exons (±10 kb) that could be identified in larger studies and, further, provide a framework for assessing the potential for replication when combining results from multiple studies.

Strong Genetic Overlaps Between Dimensional and Categorical Models of Bipolar Disorders in a Family Sample.

Background: Bipolar disorder (BD) presents with a wide range of symptoms that vary among relatives, casting doubt on categorical illness models. To address this uncertainly, we investigated the heritability and genetic relationships between categorical and dimensional models of BD in a family sample. Methods: Participants in the Amish-Mennonite Bipolar Genetics (AMBiGen) study were assigned categorical mood disorder diagnoses by structured psychiatric interview and completed the Mood Disorder Questionnaire (MDQ), which assesses lifetime history of manic symptoms and associated impairment. Major MDQ dimensions were analyzed by Principal Component Analysis (PCA) in 726 participants. Heritability and genetic overlaps between categorical diagnoses and MDQ-derived dimensions were estimated with SOLAR-ECLIPSE within 432 genotyped participants. Results: MDQ scores were significantly higher among individuals diagnosed with BD and related disorders, as expected, but varied widely among relatives. PCA suggested a three-component model for the MDQ. Heritability of the MDQ score was 30% (p<0.001), evenly distributed across its three principal components. Strong and significant genetic correlations were found between categorical diagnoses and most MDQ measures. Limitations: Recruitment through probands with BD resulted in increased prevalence of BD in this sample, limiting generalizability. Unavailable genetic data reduced sample size for some analyses. Conclusion: heritability and high genetic correlations between categorical diagnoses and MDQ measures support a genetic continuity between dimensional and categorical models of BD.