Sevilla D. Detera-Wadleigh

A genome-wide association study implicates diacylglycerol kinase eta (DGKH) and several other genes in the etiology of bipolar disorder

The genetic basis of bipolar disorder has long been thought to be complex, with the potential involvement of multiple genes, but methods to analyze populations with respect to this complexity have only recently become available. We have carried out a genome-wide association study of bipolar disorder by genotyping over 550 000 single-nucleotide polymorphisms (SNPs) in two independent case-control samples of European origin. The initial association screen was performed using pooled DNA, and selected SNPs were confirmed by individual genotyping. While DNA pooling reduces power to detect genetic associations, there is a substantial cost saving and gain in efficiency. A total of 88 SNPs, representing 80 different genes, met the prior criteria for replication in both samples. Effect sizes were modest: no single SNP of large effect was detected. Of 37 SNPs selected for individual genotyping, the strongest association signal was detected at a marker within the first intron of diacylglycerol kinase eta (DGKH; P=1.5 × 10−8, experiment-wide P<0.01, OR=1.59). This gene encodes DGKH, a key protein in the lithium-sensitive phosphatidyl inositol pathway. This first genome-wide association study of bipolar disorder shows that several genes, each of modest effect, reproducibly influence disease risk. Bipolar disorder may be a polygenic disease.

G72/G30 in Schizophrenia and Bipolar Disorder: Review and Meta-analysis

Association of the G72/G30 locus with schizophrenia and bipolar disorder has now been reported in several studies. The G72/G30 locus may be one of several that account for the evidence of linkage that spans a broad region of chromosome 13q. However, the story of G72/G30 is complex. Our meta-analysis of published association studies shows highly significant evidence of association between nucleotide variations in the G72/G30 region and schizophrenia, along with compelling evidence of association with bipolar disorder. But the associated alleles and haplotypes are not identical across studies, and some strongly associated variants are located approximately 50 kb telomeric of G72. Interestingly, G72 and G30 are transcribed in opposite directions; hence, their transcripts could cross-regulate translation. A functional native protein and functional motifs for G72 or G30 remain to be demonstrated. The interaction of G72 with d-amino acid oxidase, itself of interest as a modulator of N-methyl-d-aspartate receptors through regulation of d-serine levels, has been reported in one study and could be a key functional link that deserves further investigation. The association findings in the G72/G30 region, among the most compelling in psychiatry, may expose an important molecular pathway involved in susceptibility to schizophrenia and bipolar disorder.

Initial genome scan of the nimh genetics initiative bipolar pedigrees: Chromosomes 1, 6, 8, 10, and 12

A report on an initial genome screen on 540 individuals in 97 families was collected as part of the NIMH Genetics Initiative on Bipolar Disorder. Families were ascertained to be informative for genetic linkage and underwent a common ascertainment and assessment protocol at four clinical sites. The sample was genotyped for 65 highly polymorphic markers from chromosomes 1, 6, 8, 10, and 12. The average intermarker interval was 16 cM. Genotypic data was analyzed using affected sib pair, multipoint affected sib pair, and pedigree analysis methods. Multipoint methods gave lod scores of approximately two on chromosomes 1, 6, and 10. The peak lod score on chromosome 6 occurred at the end of the q-arm, at some distance from the 6p24-22 area previously implicated for schizophrenia. We are currently genotyping additional markers to reduce the intermarker interval around the signals. The interpretation of results from a genome screen of a complex disorder and the problem of achieving a balance between detecting false positive results and the ability to detect genes of modest effect are discussed.

Syndromes of Glucocorticoid Resistance

Dr. George P. Chrousos (Developmental Endocrinology Branch, National Institute of Child Health and Human Development [NICHD], National Institutes of Health [NIH], Bethesda, Maryland): Glucocorticoids have an important role in human physiology, and almost every tissue in the human body is affected by them [1]. Glucocorticoids are crucial for the integrity of central nervous system function and for the maintenance of cardiovascular and metabolic homeostasis [2]. Increased secretion of glucocorticoids during stress is also pivotal in altering central nervous system function [3], in preventing the inflammatory and immune response systems from over-reacting [4, 5], and in adjusting energy expenditures [6], all changes that improve chances for survival. Given this array of life-sustaining functions, the complete inability of glucocorticoids to exert their effects on target tissues would be incompatible with life; therefore, only syndromes of partial or incomplete glucocorticoid resistance exist. Several patients or members of kindreds with partial forms of this disease have been described [6-18]; they show a wide spectrum of clinical symptoms and an interesting set of pathophysiologic mechanisms (Table 1). Recent advances in our understanding of the mechanism of action of glucocorticoids at the molecular level have allowed a glimpse into the pathophysiology of resistance and have increased our awareness of the potential involvement of this condition in the pathogenesis of human disease. Table 1. Glucocorticoid Resistance in Humans: Reported Patients and Kindreds Familial Glucocorticoid Resistance: The Syndromes Pathophysiology An elaborate feedback system regulates glucocorticoid homeostasis. Of principal importance is the ability of glucocorticoids to exert negative feedback on secretion by the hypothalamic paraventricular nucleus of corticotropin-releasing hormone and arginine vasopressin, on secretion by the anterior pituitary of corticotropin, and on suprahypothalamic centers that control the activity of the hypothalamic-pituitary-adrenal axis [3, 19-21]. This complex system is activated in states of generalized glucocorticoid resistance and produces compensatory increases in corticotropin and cortisol secretion (Figure 1). Although the increased cortisol concentrations in most affected persons appear to compensate adequately for the inability of target tissues to respond to glucocorticoids, the excess corticotropin secretion results in the increased production of intermediate compounds in adrenal steroidogenesis that have salt-retaining (mineralocorticoid) activity (such as deoxycorticosterone and corticosterone [8]) and in the enhanced secretion of adrenal androgens (such as Delta 4-androstenedione, dehydroepiandrosterone, and dehydroepiandrosterone-sulfate [12]). Figure 1. Pathophysiologic mechanism of glucocorticoid resistance. Clinical Presentation The clinical presentation of patients with glucocorticoid resistance is summarized in Table 1 and is related to the pathophysiology described in Figure 1. Generally, clinical manifestations of glucocorticoid deficiency were not present in most of the patients, and most of the patients evaluated in the context of family studies were asymptomatic despite biochemical indices of excessive cortisol production. The chief complaint of members of one particular family and an additional unrelated patient, however, was chronic fatigue, which might indicate inadequate compensation by the increased glucocorticoids in certain resistant target tissues, perhaps parts of the central nervous system or the muscles. In several patients, the increased concentrations of cortisol, deoxycorticosterone, and corticosterone (all steroids known to have inherent mineralocorticoid activity) caused signs of mineralocorticoid excess, such as hypertension and hypokalemic alkalosis. Finally, increased levels of adrenal androgens caused signs of androgen excess, including masculinization in women, with manifestations affecting the skin (acne and hirsutism) and the reproductive system (oligomenorrhea, oligoanovulation, and infertility). Also, early and excessive adrenarche was associated with precocious puberty, and interference of adrenal androgens on the feedback regulation of follicle-stimulating hormone caused abnormal spermatogenesis in men with the syndrome [17]. This abnormal spermatogenesis, however, could also be explained by corticotropin-induced intratesticular growth of adrenal rests, a phenomenon known to occur in classic and late-onset congenital adrenal hyperplasia [22]. Table 2. Syndromes of Glucocorticoid Resistance These clinical manifestations were not reported in all patients with symptomatic glucocorticoid resistance, and the clinical presentation varied even within families. Two main explanations can be given for this: First, the degree of resistance, as indicated by the compensatory increases of cortisol production, has generally differed among patients, with associated variability in the production of mineralocorticoid and androgen compounds and, therefore, differing effects resulting from excess production. Second, the sensitivity of target tissues to mineralocorticoids and androgens can also vary among persons, resulting in unequal responsiveness to similar increases of circulating steroids. The factors responsible for the different sensitivity of target tissues to these hormones could be individual differences in 1) the activity of key hormone-inactivating or -activating enzymes, such as 11--ketosteroid reductase in the kidney, which inactivates cortisol, deoxycorticosterone, or corticosterone [23], or 5 -reductase and 17-ketosteroid dehydrogenase in the skin, which convert adrenal androgens to more potent metabolites [24]; or 2) the cascades of the mineralocorticoid and androgen-receptor transduction systems, which can vary at different steps [25, 26]. In addition, other genetic or epigenetic factors, such as insulin resistance or upper body (abdominal) obesity or both, may influence the clinical manifestations of the syndrome by altering pituitary and gonadal function and peripheral steroid metabolism. Diagnostic Evaluation Of major importance is the definition of appropriate criteria for the correct diagnosis of glucocorticoid resistance and its differentiation from the many diseases it mimics clinically or biochemically. These criteria are summarized in Table 2. First, the patient should not have clinical evidence of the Cushing syndrome, including the phenotypic changes and biochemical consequences of hypercortisolism. Second, indices of increased cortisol production should be present, such as increased 24-hour urinary free cortisol levels or increased 17-hydroxysteroid per gram creatinine excretion, increased plasma total and free cortisol concentrations, or an increased rate of cortisol production. Third, glucocorticoid resistance should be present as determined by dexamethasone testing using either a complete dose-response test, as previously described [8], or by using one or two doses of the compound. The results of this test should be validated against the plasma levels of dexamethasone, because absorption or metabolism of this synthetic glucocorticoid may vary from person to person. Finally, the hypothalamic-pituitary-adrenal axis should retain its normal circadian rhythmicity and its responsiveness to stressors such as hypoglycemia; however, its basal and stimulated activities should be higher than those of normal persons. Although the single-dose overnight dexamethasone suppression test may be appropriate for screening patients with potential generalized glucocorticoid resistance, its high false-positive rate of 15% to 20% makes measurement of 24-hour urinary free cortisol excretion preferable, if this syndrome is suspected. Levels above 100% (twofold) of the upper normal range are suggestive of glucocorticoid resistance or the Cushing syndrome [27]. Levels between the upper normal range and the 100% limit, however, are compatible with these diagnoses, along with a host of other states characterized by mild hypercortisolism [27, 28]. Assuming proper procedures and techniques, the syndrome of generalized glucocorticoid resistance should be easily distinguished on biochemical grounds from the chronic fatigue syndrome, essential hypertension, hyperaldosteronism, idiopathic hirsutism, polycystic ovarian disease, female infertility, precocious puberty, or male infertility, because none of these conditions is associated with hypercortisolism. It may be difficult to distinguish this syndrome in its mild biochemical form (increases in urinary free cortisol up to 100% of the upper normal range) from other mild forms of hypercortisolism, such as mild or early Cushing syndrome with a lack of or borderline manifestations of hypercortisolism, hypercortisolemic melancholic depression, anorexia nervosa, chronic active alcoholism, and hypercortisolism in persons who exercise heavily [27, 28]. In the case of mild or early Cushing syndrome, the absence of circadian rhythmicity and lack of responsiveness of plasma cortisol during an insulin tolerance test should aid the physician in diagnosing this condition. The patients clinical course, which is frequently characterized by progressive deterioration and development of the classic Cushing phenotype, should allow eventual differentiation. The history or concurrent symptomatology and the dependence of the hypercortisolism on the actual state of the condition should differentiate glucocorticoid resistance from the other states. Therapy Synthetic glucocorticoids with minimal intrinsic mineralocorticoid activity, such as dexamethasone, provide a rational treatment for familial glucocorticoid resistance. These patients should receive oral doses of dexamethasone, usually ranging between 1 and 3 mg/d, that are clearly pharmacologic for normal persons but are equivalent to glucocorticoid replacement for the glucocorticoid-resistance

Initial genomic scan of the NIMH genetics initiative bipolar pedigrees: Chromosomes 3, 5, 15, 16, 17, and 22

As part of the four-center NIMH Genetics Initiative on Bipolar Disorder we carried out a genomic scan of chromosomes 3, 5, 15, 16,17, and 22. Genotyping was performed on a set of 540 DNAs from 97 families, enriched for affected relative pairs and parents where available. We report here the results of the initial 74 markers that have been typed on this set of DNAs. The average distance between markers (theta) was 12.3 cM. Nonparametric analysis of excess allele sharing among affected sibling pairs used the SIBPAL program of the S.A.G.E. package to test three hierarchical models of affected status. D16S2619 gave some evidence of linkage to bipolar disorder, with P = 0.006 for Model II (in which bipolar 1, bipolar 2 and schizoaffective-bipolar type individuals are considered affected). Nearby markers also showed increased allele sharing. A second interesting region was toward the telomere of chromosome 5q, where D5S1456 and nearby markers showed increased allele sharing; for D5S1456, P = 0.05, 0.015 and 0.008 as the models of affected status become more broad. MOD score analysis also supported the possible presence of a susceptibility locus in this region of chromosome 5. A pair of adjacent markers on chromosome 3, D3S2405 and D3S3038, showed a modest increased allele sharing in the broad model. Several isolated markers had excess allele sharing at the P < 0.05 level under a single model. D15S217 showed a MOD score of 2.37 (P < 0.025). Multipoint analysis flagged the region of chromosome 22 around D22S533 as the most interesting. Thus, several regions showed modest evidence for linkage to bipolar disorder in this initial genomic scan of these chromosomes, including broad regions near previous reports of possible linkage.

Meta-analysis of genome-wide association data identifies a risk locus for major mood disorders on 3p21.1.

The major mood disorders, which include bipolar disorder and major depressive disorder (MDD), are considered heritable traits, although previous genetic association studies have had limited success in robustly identifying risk loci. We performed a meta-analysis of five case-control cohorts for major mood disorder, including over 13,600 individuals genotyped on high-density SNP arrays. We identified SNPs at 3p21.1 associated with major mood disorders (rs2251219, P = 3.63 × 10−8; odds ratio = 0.87; 95% confidence interval, 0.83–0.92), with supportive evidence for association observed in two out of three independent replication cohorts. These results provide an example of a shared genetic susceptibility locus for bipolar disorder and MDD.

Molecular cytogenetic fingerprinting of esophageal squamous cell carcinoma by comparative genomic hybridization reveals a consistent pattern of chromosomal alterations.

Esophageal cancer is the third most prevalent gastrointestinal malignancy in the world. The tumor responds poorly to various therapeutic regimens and the genetic events underlying esophageal carcinogenesis are not well understood. To identify overall chromosomal aberrations in esophageal squamous cell carcinoma, we performed comparative genomic hybridization (CGH). All 17 tumor samples were found to exhibit multiple gains and losses involving different chromosomal regions. The frequency of chromosomal loss associated with this type of tumor was as follows: in 2q (100%), 3p (100%), 13q (100%), Xq (94%), 4 (82%), 5q (82%), 18q (76%), 9p (76%), 6q (70%), 12q (70%), 14q (65%), 11q (59%), and 1p (53%). Interstitial deletions on 1p, 3p, 5q, 6q, 11q, and 12q were detected also. Chromosomal gains were displayed by chromosomes and chromosome areas: 19 (100%), 20q (94%), 22 (94%), 16p (65%), 17 (59%), 12q (59%), 8q (53%), 9q (53%), and 3q (50%). Two sites showing apparent amplification were 11q (70%) and 5p15 (47%). To validate the CGH data, we isolated a BAC clone mapping to 18q12.1. This clone was used as a probe in interphase fluorescence in situ hybridization of tumor touch preparations and allelic loss was clearly revealed. This study represents the first whole‐genome analysis in esophageal squamous cell carcinoma for associated chromosomal aberrations that may be involved in either the genesis or progression of this malignancy. Genes Chromosomes Cancer 25:160–168, 1999.

Two variants in Ankyrin 3 ( ANK3 ) are independent genetic risk factors for bipolar disorder

Two recent reports have highlighted ANK3 as a susceptibility gene for bipolar disorder (BD). We first reported association between BD and the ANK3 marker rs9804190 in a genome-wide association study (GWAS) of two independent samples (Baum et al., 2008). Subsequently, a meta-analysis of GWAS data based on samples from the US and the UK reported association with a different ANK3 marker, rs10994336 (Ferreira et al., 2008). The markers lie about 340 kb apart in the gene. Here, we test both markers in additional samples and characterize the contribution of each marker to BD risk. Our previously reported findings at rs9804190, which had been based on DNA pooling, were confirmed by individual genotyping in the National Institute of Mental Health (NIMH) waves 1–4 (P=0.05; odds ratio (OR)=1.24) and German (P=0.0006; OR=1.34) samples. This association was replicated in an independent US sample known as NIMH wave 5 (466 cases, 212 controls; P=0.017; OR=1.38). A random-effects meta-analysis of all three samples was significant (P=3 × 10−6; OR=1.32), with no heterogeneity. Individual genotyping of rs10994336 revealed a significant association in the German sample (P=0.0001; OR=1.70), and similar ORs in the NIMH 1–4 and NIMH 5 samples that were not significant at the P<0.05 level. Meta-analysis of all three samples supported an association with rs10994336 (P=1.7 × 10−5; OR=1.54), again with no heterogeneity. There was little linkage disequilibrium between the two markers. Further analysis suggested that each marker contributed independently to BD, with no significant marker × marker interaction. Our findings strongly support ANK3 as a BD susceptibility gene and suggest true allelic heterogeneity.

Autistic-like phenotypes in Cadps2-knockout mice and aberrant CADPS2 splicing in autistic patients

Autism, characterized by profound impairment in social interactions and communicative skills, is the most common neurodevelopmental disorder, and its underlying molecular mechanisms remain unknown. Ca(2+)-dependent activator protein for secretion 2 (CADPS2; also known as CAPS2) mediates the exocytosis of dense-core vesicles, and the human CADPS2 is located within the autism susceptibility locus 1 on chromosome 7q. Here we show that Cadps2-knockout mice not only have impaired brain-derived neurotrophic factor release but also show autistic-like cellular and behavioral phenotypes. Moreover, we found an aberrant alternatively spliced CADPS2 mRNA that lacks exon 3 in some autistic patients. Exon 3 was shown to encode the dynactin 1-binding domain and affect axonal CADPS2 protein distribution. Our results suggest that a disturbance in CADPS2-mediated neurotrophin release contributes to autism susceptibility.

Findings in an independent sample support an association between bipolar affective disorder and the G72/G30 locus on chromosome 13q33

Markers near the nested genes G72 and G30 on chromosome 13q33 have been implicated in the etiology of schizophrenia and, recently, bipolar affective disorder (BPAD). Hattori et al (2003) reported that single-nucleotide polymorphisms (SNPs) near the G72/G30 locus were associated with BPAD in a sample of 22 pedigrees, and that SNP haplotypes were associated in a second, larger sample of triads. The present study attempts to replicate this finding in an independent case–control sample. Six SNPs near the G72/G30 locus, including the most strongly associated markers in the previous study, were tested in 139 cases and 113 ethnically matched controls. Significant association was detected between BPAD and two adjacent SNPs (smallest P=0.007; global P=0.024). Haplotype analysis produced additional support for association (smallest P=0.004; global P=0.004). Analysis of 31 unlinked microsatellite markers detected no population stratification in the cases or controls studied. Although the associated alleles and haplotypes differ from those previously reported, these new results provide further evidence, in an independent sample, for an association between BPAD and genetic variation in the vicinity of the genes G72 and G30.