Berit Kerner

Genetics of bipolar disorder

Bipolar disorder is a common, complex genetic disorder, but the mode of transmission remains to be discovered. Many researchers assume that common genomic variants carry some risk for manifesting the disease. The research community has celebrated the first genome-wide significant associations between common single nucleotide polymorphisms (SNPs) and bipolar disorder. Currently, attempts are under way to translate these findings into clinical practice, genetic counseling, and predictive testing. However, some experts remain cautious. After all, common variants explain only a very small percentage of the genetic risk, and functional consequences of the discovered SNPs are inconclusive. Furthermore, the associated SNPs are not disease specific, and the majority of individuals with a “risk” allele are healthy. On the other hand, population-based genome-wide studies in psychiatric disorders have rediscovered rare structural variants and mutations in genes, which were previously known to cause genetic syndromes and monogenic Mendelian disorders. In many Mendelian syndromes, psychiatric symptoms are prevalent. Although these conditions do not fit the classic description of any specific psychiatric disorder, they often show nonspecific psychiatric symptoms that cross diagnostic boundaries, including intellectual disability, behavioral abnormalities, mood disorders, anxiety disorders, attention deficit, impulse control deficit, and psychosis. Although testing for chromosomal disorders and monogenic Mendelian disorders is well established, testing for common variants is still controversial. The standard concept of genetic testing includes at least three broad criteria that need to be fulfilled before new genetic tests should be introduced: analytical validity, clinical validity, and clinical utility. These criteria are currently not fulfilled for common genomic variants in psychiatric disorders. Further work is clearly needed before genetic testing for common variants in psychiatric disorders should be established.

Genome-Wide Association Study in Bipolar Patients Stratified by Co-Morbidity

Background Bipolar disorder is a severe psychiatric disorder with high heritability. Co-morbid conditions are common and might define latent subgroups of patients that are more homogeneous with respect to genetic risk factors. Methodology In the Caucasian GAIN bipolar disorder sample of 1000 cases and 1034 controls, we tested the association of single nucleotide polymorphisms with patient subgroups defined by co-morbidity. Results Bipolar disorder with psychosis and/or substance abuse in the absence of alcohol dependence was associated with the rare variant rs1039002 in the vicinity of the gene phosphodiesterase 10A (PDE10A) on chromosome 6q27 (p = 1.7×10−8). PDE10A has been implicated in the pathophysiology of psychosis. Antagonists to the encoded protein are currently in clinical testing. Another rare variant, rs12563333 (p = 5.9×10−8) on chromosome 1q41 close to the MAP/microtubule affinity-regulating kinase 1 (MARK1) gene, approached the genome-wide level of significance in this subgroup. Homozygotes for the minor allele were present in cases and absent in controls. Bipolar disorder with alcohol dependence and other co-morbidities was associated with SNP rs2727943 (p = 3.3×10−8) on chromosome 3p26.3 located between the genes contactin-4 precursor (BIG-2) and contactin 6 (CNTN6). All three associations were found under the recessive genetic model. Bipolar disorder with low probability of co-morbid conditions did not show significant associations. Conclusion Conceptualizing bipolar disorder as a heterogeneous disorder with regard to co-morbid conditions might facilitate the identification of genetic risk alleles. Rare variants might contribute to the susceptibility to bipolar disorder.

Polymorphisms in the GRIA1 gene region in psychotic bipolar disorder

We reported previously a significant linkage signal between psychotic bipolar disorder (BP) and microsatellite markers on chromosome 5q31–34 in the National Institute of Mental Health Bipolar Genetics Initiative (NIMH‐BPGI) data set, Wave 1. In an attempt to fine‐map this linkage signal we genotyped 1,134 single nucleotide polymorphisms (SNPs) under the linkage peak in 23 informative families (131 individuals) with evidence of linkage. We tested family based association in the presence of linkage with the computer software package FBAT. The most significant association in these families was with a SNP in the second intron of GRIA1 (α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazole proprionic acid (AMPA) subunit 1 receptor gene) (rs490922, Z‐score = 3.3, P = 0.001). The analysis of 37 additional families with psychotic BP from NIMH‐BPGI data sets, Waves 2, 3, and 4 revealed a signal at a SNP in intron 5 of the GRIA1 gene (rs4385264, Z‐score = 3.2, P‐value = 0.002). A combined analysis of all 60 families continued to support evidence for association of GRIA1 with psychotic BP; however, individual SNPs could not be replicated across datasets. The AMPA1 receptor has been shown to influence cognitive function, such as working memory and reward learning. Our findings suggest that variations in this receptor may contribute to the pathophysiology of BP with psychotic features in some families.

Evidence of linkage to psychosis on chromosome 5q33-34 in pedigrees ascertained for bipolar disorder.

It is hypothesized that the presence of psychotic features may define a subtype of bipolar disorder that is more homogeneous in its genetic predisposition than bipolar disorder as a whole. We used psychosis as an alternative phenotype definition in a re‐analysis of the NIMH Bipolar Genetics Initiative data sets. In this analysis we selected only those families in which at least two members were diagnosed with bipolar disorder type 1 with psychotic features. This analysis identified a linkage signal on chromosome 5q33‐q34, a region previously implicated in independent linkage studies of schizophrenia and of psychosis, broadly defined. This finding is consistent with the hypothesis that susceptibility to psychosis may characterize at least a subtype of bipolar disorder.

Rare Genomic Variants Link Bipolar Disorder with Anxiety Disorders to CREB-Regulated Intracellular Signaling Pathways

Bipolar disorder is a common, complex, and severe psychiatric disorder with cyclical disturbances of mood and a high suicide rate. Here, we describe a family with four siblings, three affected females and one unaffected male. The disease course was characterized by early-onset bipolar disorder and co-morbid anxiety spectrum disorders that followed the onset of bipolar disorder. Genetic risk factors were suggested by the early onset of the disease, the severe disease course, including multiple suicide attempts, and lack of adverse prenatal or early life events. In particular, drug and alcohol abuse did not contribute to the disease onset. Exome sequencing identified very rare, heterozygous, and likely protein-damaging variants in eight brain-expressed genes: IQUB, JMJD1C, GADD45A, GOLGB1, PLSCR5, VRK2, MESDC2, and FGGY. The variants were shared among all three affected family members but absent in the unaffected sibling and in more than 200 controls. The genes encode proteins with significant regulatory roles in the ERK/MAPK and CREB-regulated intracellular signaling pathways. These pathways are central to neuronal and synaptic plasticity, cognition, affect regulation and response to chronic stress. In addition, proteins in these pathways are the target of commonly used mood-stabilizing drugs, such as tricyclic antidepressants, lithium, and valproic acid. The combination of multiple rare, damaging mutations in these central pathways could lead to reduced resilience and increased vulnerability to stressful life events. Our results support a new model for psychiatric disorders, in which multiple rare, damaging mutations in genes functionally related to a common signaling pathway contribute to the manifestation of bipolar disorder.

Toward a Deeper Understanding of the Genetics of Bipolar Disorder

Bipolar disorder is a common, complex psychiatric disorder characterized by mania and depression. The disease aggregates in families, but despite much effort, it has been difficult to delineate the basic genetic model or identify specific genetic risk factors. Not only single gene Mendelian transmission and common variant hypotheses but also multivariate threshold models and oligogenic quasi-Mendelian modes of inheritance have dominated the discussion at times. Almost complete sequence information of the human genome and falling sequencing costs now offer the opportunity to test these models in families in which the disorder is transmitted over several generations. Exome-wide sequencing studies have revealed an astonishing number of rare and potentially damaging mutations in brain-expressed genes that could have contributed to the disease manifestation. However, the statistical analysis of these data has been challenging, because genetic risk factors displayed a high degree of dissimilarity across families. This scenario is not unique to bipolar disorder, but similar results have also been found in schizophrenia, a potentially related psychiatric disorder. Recently, our group has published data which supported an oligogenic genetic model of transmission in a family with bipolar disorder. In this family, three affected siblings shared rare, damaging mutations in multiple genes, which were linked to stress response pathways. These pathways are also the target for drugs frequently used to treat bipolar disorder. This article discusses these findings in the context of previously proclaimed disease models and suggests future research directions, including biological confirmation and phenotype stratification as an approach to disease heterogeneity.

Use of Longitudinal Data in Genetic Studies in the Genome-wide Association Studies Era: Summary of Group 14

Participants analyzed actual and simulated longitudinal data from the Framingham Heart Study for various metabolic and cardiovascular traits. The genetic information incorporated into these investigations ranged from selected single‐nucleotide polymorphisms to genome‐wide association arrays. Genotypes were incorporated using a broad range of methodological approaches including conditional logistic regression, linear mixed models, generalized estimating equations, linear growth curve estimation, growth modeling, growth mixture modeling, population attributable risk fraction based on survival functions under the proportional hazards models, and multivariate adaptive splines for the analysis of longitudinal data. The specific scientific questions addressed by these different approaches also varied, ranging from a more precise definition of the phenotype, bias reduction in control selection, estimation of effect sizes and genotype associated risk, to direct incorporation of genetic data into longitudinal modeling approaches and the exploration of population heterogeneity with regard to longitudinal trajectories. The group reached several overall conclusions: (1) The additional information provided by longitudinal data may be useful in genetic analyses. (2) The precision of the phenotype definition as well as control selection in nested designs may be improved, especially if traits demonstrate a trend over time or have strong age‐of‐onset effects. (3) Analyzing genetic data stratified for high‐risk subgroups defined by a unique development over time could be useful for the detection of rare mutations in common multifactorial diseases. (4) Estimation of the population impact of genomic risk variants could be more precise. The challenges and computational complexity demanded by genome‐wide single‐nucleotide polymorphism data were also discussed. Genet. Epidemiol. 33 (Suppl. 1):S93–S98, 2009.

Getting ready for the human phenome project: the 2012 forum of the human variome project

A forum of the Human Variome Project (HVP) was held as a satellite to the 2012 Annual Meeting of the American Society of Human Genetics in San Francisco, California. The theme of this meeting was “Getting Ready for the Human Phenome Project.” Understanding the genetic contribution to both rare single‐gene “Mendelian” disorders and more complex common diseases will require integration of research efforts among many fields and better defined phenotypes. The HVP is dedicated to bringing together researchers and research populations throughout the world to provide the resources to investigate the impact of genetic variation on disease. To this end, there needs to be a greater sharing of phenotype and genotype data. For this to occur, many databases that currently exist will need to become interoperable to allow for the combining of cohorts with similar phenotypes to increase statistical power for studies attempting to identify novel disease genes or causative genetic variants. Improved systems and tools that enhance the collection of phenotype data from clinicians are urgently needed. This meeting begins the HVPs effort toward this important goal.

Comorbid substance use disorders in schizophrenia: a latent class approach.

Schizophrenia is a complex psychiatric disorder with a characteristic disease course and heterogeneous etiology. While substance use disorders and a family history of psychosis have individually been identified as risk factors for schizophrenia, it is less well understood if and how these factors are related. To address this deficiency, we examined the relationship between substance use disorders and family history of psychosis in a sample of 1219 unrelated patients with schizophrenia. The lifetime rate of substance use disorders in this sample was 50%, and 30% had a family history of psychosis. Latent class mixture modeling identified three distinct patient subgroups: (1) individuals with low probability of substance use disorders; (2) patients with drug and alcohol abuse, but no symptoms of dependence; and (3) patients with substance dependence. Substance use was related to being male, to a more severe disease course, and more acute symptoms at assessment, but not to an earlier age of onset of schizophrenia or a specific pattern of positive and negative symptoms. Furthermore, substance use in schizophrenia was not related to a family history of psychosis. The results suggest that substance use in schizophrenia is an independent risk factor for disease severity and onset.

Bipolar disorder and diabetes mellitus: evidence for disease-modifying effects and treatment implications

BackgroundBipolar disorder refers to a group of chronic psychiatric disorders of mood and energy levels. While dramatic psychiatric symptoms dominate the acute phase of the diseases, the chronic course is often determined by an increasing burden of co-occurring medical conditions. High rates of diabetes mellitus in patients with bipolar disorder are particularly striking, yet unexplained. Treatment and lifestyle factors could play a significant role, and some studies also suggest shared pathophysiology and risk factors.ObjectiveIn this systematic literature review, we explored data around the relationship between bipolar disorder and diabetes mellitus in recently published population-based cohort studies with special focus on the elderly.MethodsA systematic search in the PubMed database for the combined terms “bipolar disorder” AND “elderly” AND “diabetes” in papers published between January 2009 and December 2015 revealed 117 publications; 7 studies were large cohort studies, and therefore, were included in our review.ResultsWe found that age- and gender- adjusted risk for diabetes mellitus was increased in patients with bipolar disorder and vice versa (odds ratio range between 1.7 and 3.2).DiscussionOur results in large population-based cohort studies are consistent with the results of smaller studies and chart reviews. Even though it is likely that heterogeneous risk factors may play a role in diabetes mellitus and in bipolar disorder, growing evidence from cell culture experiments and animal studies suggests shared disease mechanisms. Furthermore, disease-modifying effects of bipolar disorder and diabetes mellitus on each other appear to be substantial, impacting both treatment response and outcomes.ConclusionsThe risk of diabetes mellitus in patients with bipolar disorder is increased. Our findings add to the growing literature on this topic. Increasing evidence for shared disease mechanisms suggests new disease models that could explain the results of our study. A better understanding of the complex relationship between bipolar disorder and diabetes mellitus could lead to novel therapeutic approaches and improved outcomes.