Population-based linkage analysis of schizophrenia and bipolar case-control cohorts identifies a potential susceptibility locus on 19q13

An exploration of linkage fine-mapping on sequences from case-control studies

Linkage analysis maps genetic loci for a heritable trait by identifying genomic regions with excess relatedness among individuals with similar trait values. Analysis may be conducted on related individuals from families, or on samples of unrelated individuals from a population. For allelically heterogeneous traits, population-based linkage analysis can be more powerful than genotypic-association analysis. Here, we focus on linkage analysis in a population sample, but use sequences rather than individuals as our unit of observation. Earlier investigations of sequence-based linkage mapping relied on known sequence relatedness, whereas we infer relatedness from the sequence data. We propose two ways to associate similarity in relatedness of sequences with similarity in their trait values and compare the resulting linkage methods to two genotypic-association methods. We also introduce a procedure to label case sequences as potential carriers or noncarriers of causal variants after an association has been found. This post hoc labeling of case sequences is based on inferred relatedness to other case sequences. Our simulation results indicate that methods based on sequence relatedness improve localization and perform as well as genotypic-association methods for detecting rare causal variants. Sequence-based linkage analysis therefore has potential to fine-map allelically heterogeneous disease traits.

A functional SNP rs895819 on pre-miR-27a is associated with bipolar disorder by targeting NCAM1

The aberrant expression or genomic mutations of microRNA are associated with several human diseases. This study analyzes the relationship between genetic variations of miRNA and schizophrenia or bipolar disorder. We performed case-control studies for ten SNPs in a total sample of 1584 subjects. All these ten SNPs were on or near mature microRNAs. We identified the association between bipolar disorder and the T/C polymorphism at rs895819. To illustrate the function of miR-27a, we constructed several miR-27a knockout (KO) cell lines, determined candidates of miR-27a, and then verified NCAM1 as a target gene of miR-27a. Further studies revealed that the T/C polymorphism on miR-27a led to the differential expression of mature and precursor miR-27a without affecting the expression of primary miR-27a. Furthermore, the C mutation on pre-miR-27a suppresses cell migration and dopamine expression levels. Our study highlights the importance of miR-27a and its polymorphism at rs895819 in bipolar disorder.

A T/C variant in miR-27a is associated with bipolar disorder, potentially by reducing the ability of this microRNA to target important neurodevelopmental genes like NCAM1.

DNA methylation of the KLK8 gene in depression symptomatology

Background

Depression is a common, complex, and debilitating mental disorder estimated to be under-diagnosed and insufficiently treated in society. Liability to depression is influenced by both genetic and environmental risk factors, which are both capable of impacting DNA methylation (DNAm). Accordingly, numerous studies have researched for DNAm signatures of this disorder. Recently, an epigenome-wide association study of monozygotic twins identified an association between DNAm status in the KLK8 (neuropsin) promoter region and severity of depression symptomatology.

Methods

In this study, we aimed to investigate: (i) if blood DNAm levels, quantified by pyrosequencing, at two CpG sites in the KLK8 promoter are associated with depression symptomatology and depression diagnosis in an independent clinical cohort and (ii) if KLK8 DNAm levels are associated with depression, postpartum depression, and depression symptomatology in four independent methylomic cohorts, with blood and brain DNAm quantified by either MBD-seq or 450 k methylation array.

Results

DNAm levels in KLK8 were not significantly different between depression cases and controls, and were not significantly associated with any of the depression symptomatology scores after correction for multiple testing (minimum p value for KLK8 CpG1 = 0.12 for ‘Depressed mood,’ and for CpG2 = 0.03 for ‘Loss of self-confidence with other people’). However, investigation of the link between KLK8 promoter DNAm levels and depression-related phenotypes collected from four methylomic cohorts identified significant association (p value < 0.05) between severity of depression symptomatology and blood DNAm levels at seven CpG sites.

Conclusions

Our findings suggest that variance in blood DNAm levels in KLK8 promoter region is associated with severity of depression symptoms, but not depression diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01184-5.

Alternative Applications of Genotyping Array Data Using Multivariant Methods

One of the forerunners that pioneered the revolution of high-throughput genomic technologies is the genotyping microarray technology, which can genotype millions of single-nucleotide variants simultaneously. Owing to apparent benefits, such as high speed, low cost, and high throughput, the genotyping array has gained lasting applications in genome-wide association studies (GWAS) and thus accumulated an enormous amount of data. Empowered by continuous manufactural upgrades and analytical innovation, unconventional applications of genotyping array data have emerged to address more diverse genetic problems, holding promise of boosting genetic research into human diseases through the re-mining of the rich accumulated data. Here, we review several unconventional genotyping array analysis techniques that have been built on the idea of large-scale multivariant analysis and provide empirical application examples. These unconventional outcomes of genotyping arrays include polygenic score, runs of homozygosity (ROH)/heterozygosity ratio, distant pedigree computation, and mitochondrial DNA (mtDNA) copy number inference.

Transgenerational Interaction of Alzheimer's Disease with Schizophrenia through Amyloid Evolvability

Alzheimer's disease (AD), the most common neurodegenerative dementia, leads to memory dysfunction due to widespread neuronal loss associated with aggregation of amyloidogenic proteins (APs), while schizophrenia (SCZ) represents a major psychiatric disorder characterized by delusions, hallucinations, and other cognitive abnormalities, the underlying mechanisms of which remain obscure. Although AD and SCZ partially overlap in terms of psychiatric symptoms and some aspects of cognitive impairment, the causal relationship between AD and SCZ is unclear. Based on the similarity of APs with yeast prion in terms of stress-induced protein aggregation, we recently proposed that evolvability of APs might be an epigenetic phenomenon to transmit stress information of parental brain to cope with the stressors in offspring. Although amyloid evolvability may be beneficial in evolution, AD might be manifested during parental aging as the mechanism of antagonistic pleiotropy phenomenon. Provided that accumulating evidence implicates stress as an important factor in SCZ, the main objective of this paper is to better understand the possible connection of AD and SCZ through amyloid evolvability. Hypothetically, the delivery of information of stress by APs may be less efficient under the decreased evolvability conditions such as disease-modifying treatment, leading to SCZ in offspring. Conversely, the increased evolvability conditions including gene mutations of APs are supposed to be beneficial for offspring, but might lead to AD in parents. Collectively, AD and SCZ might transgenerationally interfere with each other through amyloid evolvability, and this could explain why both AD and SCZ have not been selected out through evolution.

Epigenome-wide association study of depression symptomatology in elderly monozygotic twins

Depression is a severe and debilitating mental disorder diagnosed by evaluation of affective, cognitive and physical depression symptoms. Severity of these symptoms strongly impacts individual's quality of life and is influenced by a combination of genetic and environmental factors. One of the molecular mechanisms allowing for an interplay between these factors is DNA methylation, an epigenetic modification playing a pivotal role in regulation of brain functioning across lifespan. The aim of this study was to investigate if there are DNA methylation signatures associated with depression symptomatology in order to identify molecular mechanisms contributing to pathophysiology of depression. We performed an epigenome-wide association study (EWAS) of continuous depression symptomatology score measured in a cohort of 724 monozygotic Danish twins (346 males, 378 females). Through EWAS analyses adjusted for sex, age, flow-cytometry based blood cell composition, and twin relatedness structure in the data we identified depression symptomatology score to be associated with blood DNA methylation levels in promoter regions of neuropsin (KLK8, p-value = 4.7 × 10^-7) and DAZ associated protein 2 (DAZAP2, p-value = 3.13 × 10^-8) genes. Other top associated probes were located in gene bodies of MAD1L1 (p-value = 5.16 × 10^-6), SLC29A2 (p-value = 6.15 × 10^-6) and AKT1 (p-value = 4.47 × 10^-6), all genes associated before with development of depression. Additionally, the following three measures (a) DNAmAge (calculated with Horvath and Hannum epigenetic clock estimators) adjusted for chronological age, (b) difference between DNAmAge and chronological age, and (c) DNAmAge acceleration were not associated with depression symptomatology score in our cohort. In conclusion, our data suggests that depression symptomatology score is associated with DNA methylation levels of genes implicated in response to stress, depressive-like behaviors, and recurrent depression in patients, but not with global DNA methylation changes across the genome.

Co-aggregation of major psychiatric disorders in individuals with first-degree relatives with schizophrenia: a nationwide population-based study

A previous genetic study has suggested that schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) share common disease-associated genes. However, whether individuals with first-degree relatives (FDRs) with schizophrenia have a higher risk of these major psychiatric disorders requires further investigation. This study used Taiwan's National Health Insurance Research Database and identified 151 650 patients with schizophrenia and 227 967 individuals with FDRs with schizophrenia. The relative risks (RRs) of schizophrenia and other major psychiatric disorders were assessed in individuals with FDRs with schizophrenia. The individuals with FDRs with schizophrenia exhibited higher RRs (95% confidence interval) of major psychiatric disorders, namely schizophrenia (4.76, 4.65-4.88), bipolar disorder (3.23, 3.12-3.35), major depressive disorder (2.05, 2.00-2.10), ASD (2.55, 2.35-2.77) and ADHD (1.31, 1.25-1.37) than were found in the total population. Several sensitivity analyses were conducted to confirm these results. A dose-dependent relationship was observed between the risks of major psychiatric disorders and the numbers of FDRs with schizophrenia. The increased risks of major psychiatric disorders were consistent in different family relationships, namely among parents, offspring, siblings and twins. Our study supports the familial dose-dependent co-aggregation of schizophrenia, bipolar disorder, major depressive disorder, ASD and ADHD, and our results may prompt governmental public health departments and psychiatrists to focus on the mental health of individuals with FDRs with schizophrenia.

Plasma levels of Th17-related cytokines and complement C3 correlated with aggressive behavior in patients with schizophrenia

Increasing evidence indicates that immune inflammatory processes, especially autoimmune reaction, should be considered in the pathophysiology of schizophrenia and aggressive behavior. The present study aimed to explore the correlation between immune factors (C3 and Th17-related cytokines) and aggressive behavior in schizophrenia patients. Forty schizophrenia patients and forty age- and gender-matched healthy controls participated in the study. Blood samples were assessed by ELISA upon enrollment. Positive and negative syndrome scale (PANSS) and modified overt aggression scale (MOAS) were used to estimate the severity and aggressive symptoms of schizophrenia patients. Plasma levels of IL-17, IL-23, and TGF-β1 in schizophrenia patients were significantly higher than those in healthy controls [(37.63±17.82) vs. (29.34±10.38)pg/ml, p=0.02; (101.40±135.26) vs. (13.09±5.94) pg/ml, p=0.01; (2864.57±2163.61) vs. (1839.69±1797.73)pg/ml, p=0.04], whereas C3 levels were significantly lower in schizophrenia patients [( 120,479.67± 65,612.50) vs. ( 208,060.21± 217,008.21)ng/ml, p=0.02]. IL-17, IL-23, and TGF-β1 levels were positively related to total scores of MOAS (p=0.02, p=0.02 and p=0.03, respectively) and PANSS (p=0.04, p=0.04 and p=0.02, respectively), whereas C3 levels were negatively related to total PANSS scores (p=0.03). IL-17 and IL-23 levels were positively correlated with PANSS excited component scores (p=0.04 and p=0.01, respectively). Our findings suggested that the Th17-related cytokine levels were positively related to the severity of schizophrenia and aggressive behavior, whereas C3 levels were negatively related to the severity of schizophrenia. This study demonstrated that elevated levels of Th17-related cytokines and decreased levels of C3 could be potential biomarkers for schizophrenia and aggressive behavior.

Identity-by-descent mapping for diastolic blood pressure in unrelated Mexican Americans

Population-based identity by descent (IBD) mapping is a statistical method for detection of genetic loci that share an ancestral segment among “unrelated” pairs of individuals for a disease. As a complementary method to genome-wide association studies, IBD mapping is robust to allelic heterogeneity and may identify rare inherited variants when combined with sequence data.

Our objective is to identify the causal genes for diastolic blood pressure (DBP). We applied a population-based IBD mapping method to 105 unrelated individuals selected from the family data provided for the Genetic Analysis Workshop 19. Using the genome-wide association study data (ie, the microarray data), chromosome 3 was scanned for IBD sharing segments among all pairs of these individuals. At the chromosomal region with the most significant relationship between IBD sharing and DBP, the whole genome sequence data were examined to identify the risk variants for DBP.

The most significant chromosomal region that was identified to have a relationship between the IBD sharing and DBP was at 3q12.3 (p = 0.0016), although it did not achieve the chromosome-wide significance level (p = 0.00012). This chromosomal region contains 1 gene, ZPLD1, which has been reported to be associated with cerebral cavernous malformations, a disease with enlarged small blood vessels (capillaries) in the brain. Although 24 deleterious variants were identified at this region, no significant association was found between these variants and DBP (p = 0.40).

We presented a mapping strategy which combined a population-based IBD mapping method with sequence data analyses. One gene was located at a chromosomal region identified by this method for DBP. However, further study with a large sample size is needed to assess this result.

Complement levels and anti-C1q autoantibodies in patients with neuropsychiatric systemic lupus erythematosus

Objective

The objective of this paper is to analyse serum levels of anti-C1q, C1q circulating immune complexes (CIC), complement activation and complement components in systemic lupus erythematosus (SLE) patients during the first central nervous system neuropsychiatric (NP) event and to define the possible association between these results and clinical and laboratory characteristics.

Methods

A total of 280 patients suspected of having NP involvement due to SLE were recruited in the Leiden NPSLE-clinic. All SLE patients were classified according to the ACR 1982 revised criteria for the classification of SLE. The clinical disease activity was measured by the SLE Disease Activity Index 2000 (SLEDAI-2K) and NP diagnoses were classified according to the 1999 ACR case definitions for NPSLE. We measured in serum of all patients anti-C1q and C1q CIC levels, the activation capacity of complement (CH50 and AP50) and different complement components (C1q, C3, C4).

Results

In 92 patients the symptoms were attributed to SLE. NPSLE patients consisted of 63 patients with focal NPSLE and 34 patients with diffuse NPSLE. Anti-C1q antibodies were significantly higher and CH50, AP50 and C3 were significantly lower in NPSLE patients compared with SLE patients without NPSLE. This association was specially marked for diffuse NPSLE while no differences were found for focal NPSLE. After using potential predictors, decreased C4 remained significantly associated with focal NPSLE, but only when antiphospholipid antibodies (aPL) were included in the model. C3 and AP50 were independently associated with diffuse NPSLE. When SLEDAI-2K was included in the model these two associations were lost. When individual NPSLE syndromes were analysed, psychosis and cognitive dysfunction showed significantly lower values of complement activation capacity and all complement components. No significant associations were seen for other individual NPSLE syndromes.

Conclusion

The associations between diffuse NPSLE and anti-C1q, C3/AP50 and focal NPSLE and C4 may be explained by disease activity and the presence of aPL, respectively. The role of complement activation and complement components in lupus psychosis and cognitive dysfunction merits further research.

Analysis of Shared Haplotypes amongst Palauans Maps Loci for Psychotic Disorders to 4q28 and 5q23-q31

To localize genetic variation affecting risk for psychotic disorders in the population of Palau, we genotyped DNA samples from 203 Palauan individuals diagnosed with psychotic disorders, broadly defined, and 125 control subjects using a genome-wide single nucleotide polymorphism array. Palau has unique features advantageous for this study: due to its population history, Palauans are substantially interrelated; affected individuals often, but not always, cluster in families; and we have essentially complete ascertainment of affected individuals. To localize risk variants to genomic regions, we evaluated long-shared haplotypes, ≥10 Mb, identifying clusters of affected individuals who share such haplotypes. This extensive sharing, typically identical by descent, was significantly greater in cases than population controls, even after controlling for relatedness. Several regions of the genome exhibited substantial excess of shared haplotypes for affected individuals, including 3p21, 3p12, 4q28, and 5q23-q31. Two of these regions, 4q28 and 5q23-q31, showed significant linkage by traditional LOD score analysis and could harbor variants of more sizeable risk for psychosis or a multiplicity of risk variants. The pattern of haplotype sharing in 4q28 highlights <i>PCDH10</i>, encoding a cadherin-related neuronal receptor, as possibly involved in risk.

A significant risk locus on 19q13 for bipolar disorder identified using a combined genome-wide linkage and copy number variation analysis

Background

The genetic background to bipolar disorder (BPD) has been attributed to different genetic and genomic risk factors. In the present study we hypothesized that inherited copy number variations (CNVs) contribute to susceptibility of BPD. We screened 637 BP-pedigrees from the NIMH Genetic Initiative and gave priority to 46 pedigrees. In this subsample we performed parametric and non-parametric genome-wide linkage analyses using ~21,000 SNP-markers. We developed an algorithm to test for linkage restricted to regions with CNVs that are shared within and across families.

Results

For the combined CNV and linkage analysis, one region on 19q13 survived correction for multiple comparisons and replicates a previous BPD risk locus. The shared CNV map to the pregnancy-specific glycoprotein (PSG) gene, a gene-family not previously implicated in BPD etiology. Two SNPs in the shared CNV are likely transcription factor binding sites and are linked to expression of an F-box binding gene, a key regulator of neuronal pathways suggested to be involved in BPD etiology.

Conclusions

Our CNV-weighted linkage approach identifies a risk locus for BPD on 19q13 and forms a useful tool to future studies to unravel part of the genetic vulnerability to BPD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-015-0076-y) contains supplementary material, which is available to authorized users.

A Preliminary Genetic Analysis of Complement 3 Gene and Schizophrenia

Complement pathway activation was found to occur frequently in schizophrenia, and complement 3 (C3) plays a major role in this process. Previous studies have provided evidence for the possible role of C3 in the development of schizophrenia. In this study, we hypothesized that the gene encoding C3 (C3) may confer susceptibility to schizophrenia in Han Chinese. We analyzed 7 common single nucleotide polymorphisms (SNPs) of C3 in 647 schizophrenia patients and 687 healthy controls. Peripheral C3 mRNA expression level was measured in 23 drug-naïve patients with schizophrenia and 24 controls. Two SNPs (rs1047286 and rs2250656) that deviated from Hardy-Weinberg equilibrium were excluded for further analysis. Among the remaining 5 SNPs, there was no significant difference in allele and genotype frequencies between the patient and control groups. Logistic regression analysis showed no significant SNP-gender interaction in either dominant model or recessive model. There was no significant difference in the level of peripheral C3 expression between the drug-naïve schizophrenia patients and healthy controls. In conclusion, the results of this study do not support C3 as a major genetic susceptibility factor in schizophrenia. Other factors in AP may have critical roles in schizophrenia and be worthy of further investigation.

Drug elucidation: invertebrate genetics sheds new light on the molecular targets of CNS drugs

Many important drugs approved to treat common human diseases were discovered by serendipity, without a firm understanding of their modes of action. As a result, the side effects and interactions of these medications are often unpredictable, and there is limited guidance for improving the design of next-generation drugs. Here, we review the innovative use of simple model organisms, especially Caenorhabditis elegans, to gain fresh insights into the complex biological effects of approved CNS medications. Whereas drug discovery involves the identification of new drug targets and lead compounds/biologics, and drug development spans preclinical testing to FDA approval, drug elucidation refers to the process of understanding the mechanisms of action of marketed drugs by studying their novel effects in model organisms. Drug elucidation studies have revealed new pathways affected by antipsychotic drugs, e.g., the insulin signaling pathway, a trace amine receptor and a nicotinic acetylcholine receptor. Similarly, novel targets of antidepressant drugs and lithium have been identified in C. elegans, including lipid-binding/transport proteins and the SGK-1 signaling pathway, respectively. Elucidation of the mode of action of anesthetic agents has shown that anesthesia can involve mitochondrial targets, leak currents, and gap junctions. The general approach reviewed in this article has advanced our knowledge about important drugs for CNS disorders and can guide future drug discovery efforts.

Genome-wide association study of bipolar disorder in Canadian and UK populations corroborates disease loci including SYNE1 and CSMD1

BACKGROUND

Recently, genome-wide association studies (GWAS) for cases versus controls using single nucleotide polymorphism microarray data have shown promising findings for complex neuropsychiatric disorders, including bipolar disorder (BD).

METHODS

Here we describe a comprehensive genome-wide study of bipolar disorder (BD), cross-referencing analysis from a family-based study of 229 small families with association analysis from over 950 cases and 950 ethnicity-matched controls from the UK and Canada. Further, loci identified in these analyses were supported by pathways identified through pathway analysis on the samples.

RESULTS

Although no genome-wide significant markers were identified, the combined GWAS findings have pointed to several genes of interest that support GWAS findings for BD from other groups or consortia, such as at SYNE1 on 6q25, PPP2R2C on 4p16.1, ZNF659 on 3p24.3, CNTNAP5 (2q14.3), and CDH13 (16q23.3). This apparent corroboration across multiple sites gives much confidence to the likelihood of genetic involvement in BD at these loci. In particular, our two-stage strategy found association in both our combined case/control analysis and the family-based analysis on 1q21.2 (closest gene: sphingosine-1-phosphate receptor 1 gene, S1PR1) and on 1q24.1 near the gene TMCO1, and at CSMD1 on 8p23.2, supporting several previous GWAS reports for BD and for schizophrenia. Pathway analysis suggests association of pathways involved in calcium signalling, neuropathic pain signalling, CREB signalling in neurons, glutamate receptor signalling and axonal guidance signalling.

CONCLUSIONS

The findings presented here show support for a number of genes previously implicated genes in the etiology of BD, including CSMD1 and SYNE1, as well as evidence for previously unreported genes such as the brain-expressed genes ADCY2, NCALD, WDR60, SCN7A and SPAG16.

Lentiviral delivery of a vesicular glutamate transporter 1 (VGLUT1)-targeting short hairpin RNA vector into the mouse hippocampus impairs cognition

Glutamate is the principle excitatory neurotransmitter in the mammalian brain, and dysregulation of glutamatergic neurotransmission is implicated in the pathophysiology of several psychiatric and neurological diseases. This study utilized novel lentiviral short hairpin RNA (shRNA) vectors to target expression of the vesicular glutamate transporter 1 (VGLUT1) following injection into the dorsal hippocampus of adult mice, as partial reductions in VGLUT1 expression should attenuate glutamatergic signaling and similar reductions have been reported in schizophrenia. The VGLUT1-targeting vector attenuated tonic glutamate release in the dorsal hippocampus without affecting GABA, and selectively impaired novel object discrimination (NOD) and retention (but not acquisition) in the Morris water maze, without influencing contextual fear-motivated learning or causing any adverse locomotor or central immune effects. This pattern of cognitive impairment is consistent with the accumulating evidence for functional differentiation along the dorsoventral axis of the hippocampus, and supports the involvement of dorsal hippocampal glutamatergic neurotransmission in both spatial and nonspatial memory. Future use of this nonpharmacological VGLUT1 knockdown mouse model could improve our understanding of glutamatergic neurobiology and aid assessment of novel therapies for cognitive deficits such as those seen in schizophrenia.

Efficient clustering of identity-by-descent between multiple individuals

MOTIVATION

Most existing identity-by-descent (IBD) detection methods only consider haplotype pairs; less attention has been paid to considering multiple haplotypes simultaneously, even though IBD is an equivalence relation on haplotypes that partitions a set of haplotypes into IBD clusters. Multiple-haplotype IBD clusters may have advantages over pairwise IBD in some applications, such as IBD mapping. Existing methods for detecting multiple-haplotype IBD clusters are often computationally expensive and unable to handle large samples with thousands of haplotypes.

RESULTS

We present a clustering method, efficient multiple-IBD, which uses pairwise IBD segments to infer multiple-haplotype IBD clusters. It expands clusters from seed haplotypes by adding qualified neighbors and extends clusters across sliding windows in the genome. Our method is an order of magnitude faster than existing methods and has comparable performance with respect to the quality of clusters it uncovers. We further investigate the potential application of multiple-haplotype IBD clusters in association studies by testing for association between multiple-haplotype IBD clusters and low-density lipoprotein cholesterol in the Northern Finland Birth Cohort. Using our multiple-haplotype IBD cluster approach, we found an association with a genomic interval covering the PCSK9 gene in these data that is missed by standard single-marker association tests. Previously published studies confirm association of PCSK9 with low-density lipoprotein.

AVAILABILITY AND IMPLEMENTATION

Source code is available under the GNU Public License http://cs.au.dk/~qianyuxx/EMI/.

Nogo and Nogo receptor: relevance to schizophrenia?

The membrane protein Nogo-A and its receptor NgR have been extensively characterized for their role in restricting axonal growth, regeneration, and plasticity in the central nervous system. Recent evidence suggests that Nogo and NgR might constitute candidate genes for schizophrenia susceptibility. In this article, we critically review the possibility that dysfunctions related to Nogo-A and NgR might contribute to increased risk for schizophrenia. To this end, we consider the most important insights that have emerged from human genetic and pathological studies and from experimental animal work. Furthermore, we discuss potential mechanisms of Nogo/NgR involvement in neural circuit development and stability, and how mutations or changes in expression levels of these proteins could be developmental risk factors contributing to schizophrenia.

White matter pathology--an endophenotype for bipolar disorder?

BACKGROUND

Neuroimaging investigations of white matter abnormalities in subjects at genetic risk for bipolar disorders (BD) potentially predating the onset of BD offer several advantages. They are not confounded by the presence of illness duration or previous treatment with medication and may ultimately inform evaluation of risk for subsequent development of BD and subsequent therapeutic intervention.

DISCUSSION

Although a number of imaging studies in subjects at genetic risk for BD are available the results are conflicting and no reliable structural markers of genetic liability to bipolar disorders have been proposed. We debate that white matter pathology may be central to the genetic risk to develop BD. Thus, white matter abnormalities detectable in HR subjects but not in controls may reflect genetically driven trait markers. Similar abnormalities may be also evident both in the HR and in BD, suggesting the possibility of genetic risk factors shared by both groups. Conversely, white matter alterations observed in BD patients but not in HR and controls can be interpreted as state markers.

SUMMARY

We suggest that white matter alterations may represent endophenotypes and neurobiological markers intermediate between the underlying susceptibility genes and the clinical expression of BD.

Allele-biased expression in differentiating human neurons: implications for neuropsychiatric disorders

Stochastic processes and imprinting, along with genetic factors, lead to monoallelic or allele-biased gene expression. Stochastic monoallelic expression fine-tunes information processing in immune cells and the olfactory system, and imprinting plays an important role in development. Recent studies suggest that both stochastic events and imprinting may be more widespread than previously considered. We are interested in allele-biased gene expression occurring in the brain because parent-of-origin effects suggestive of imprinting appear to play a role in the transmission of schizophrenia (SZ) and autism spectrum disorders (ASD) in some families. In addition, allele-biased expression could help explain monozygotic (MZ) twin discordance and reduced penetrance. The ability to study allele-biased expression in human neurons has been transformed with the advent of induced pluripotent stem cell (iPSC) technology and next generation sequencing. Using transcriptome sequencing (RNA-Seq) we identified 801 genes in differentiating neurons that were expressed in an allele-biased manner. These included a number of putative SZ and ASD candidates, such as A2BP1 (RBFOX1), ERBB4, NLGN4X, NRG1, NRG3, NRXN1, and NLGN1. Overall, there was a modest enrichment for SZ and ASD candidate genes among those that showed evidence for allele-biased expression (chi-square, p = 0.02). In addition to helping explain MZ twin discordance and reduced penetrance, the capacity to group many candidate genes affecting a variety of molecular and cellular pathways under a common regulatory process – allele-biased expression – could have therapeutic implications.

IL-28B genetic variant is associated with the risk of schizophrenia in the Chinese Han population

Schizophrenia is a severe psychiatric disorder. Although its exact cause is unknown, it is widely accepted that environmental factors and genes integrate in the pathogenesis of schizophrenia. 19q13, which contains IL-28B, is a newly identified potential susceptibility locus. IL-28B is a cytokine that functionally has anti-viral activity, but, structurally, is related to the interleukin-10 family. Both virus infection and cytokine changes have been documented in schizophrenia. We selected the single-nucleotide polymorphism rs8099917, which is associated with IL-28B gene expression, to study its relationship to the susceptibility to schizophrenia. A total of 256 Chinese patients with schizophrenia and 329 healthy controls were studied. Both genotype and allele frequencies showed significant differences between patients and normal subjects (p=0.03 and p=0.04, respectively). Our study suggested that the frequency of allele T was a risk factor for the susceptibility of schizophrenia (odds ratio [OR]=1.76, 95% confidence interval [CI]=1.03-3.03). When all subjects were grouped by symptoms, both the genotype and the allele frequency were associated with patients having disorganized speech (genotype: χ(2)=5.75, p=0.02; allele: χ(2)=5.41, p=0.02, OR=3.67, 95% CI=1.14-11.82) and negative symptoms (genotype: χ(2)=5.09, p=0.02; allele: χ(2)=4.80, p=0.03, OR=1.95, 95% CI=1.06-3.56) as well as cognitive symptoms (genotype: χ(2)=5.97, p=0.02; allele: χ(2)=5.53, p=0.02, OR=2.04, 95% CI=1.11-3.74). The results in this study may lead to a better understanding of the etiology of schizophrenia.

Genetic overlap of schizophrenia and bipolar disorder in a high-density linkage survey in the Portuguese Island population

Recent family and genome-wide association studies strongly suggest shared genetic risk factors for schizophrenia (SZ) and bipolar disorder (BP). However, linkage studies have not been used to test for statistically significant genome-wide overlap between them. Forty-seven Portuguese families with sibpairs concordant for SZ, BP, or psychosis (PSY, which includes either SZ or psychotic BP) were genotyped for over 57,000 markers using the Affymetrix 50K Xba SNP array. NPL and Kong and Cox LOD scores were calculated in Merlin for all three phenotypes. Empirical significance was determined using 1,000 gene-dropping simulations. Significance of genome-wide genetic overlap between SZ and BP was determined by the number of simulated BP scans having the same number of loci jointly linked with the real SZ scan, and vice versa. For all three phenotypes, a number of regions previously linked in this sample remained so. For BP, chromosome 1p36 achieved significance (11.54-15.71 MB, LOD = 3.51), whereas it was not even suggestively linked at lower marker densities, as did chromosome 11q14.1 (89.32-90.15 MB, NPL = 4.15). Four chromosomes had loci at which both SZ and BP had NPL ≥ 1.98, which was more than would be expected by chance (empirical P = 0.01 using simulated SZ scans; 0.07 using simulated BP scans), although they did not necessarily meet criteria for suggestive linkage individually. These results suggest that high-density marker maps may provide greater power and precision in linkage studies than lower density maps. They also further support the hypothesis that SZ and BP share at least some risk alleles.

An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people

Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find rare variants are abundant (1 every 17 bases) and geographically localized, so that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. We conclude that because of rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk.

Deep sequencing of the LRRK2 gene in 14,002 individuals reveals evidence of purifying selection and independent origin of the p.Arg1628Pro mutation in Europe

Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single-nucleotide variants, 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Among Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.

Detecting rare variant associations by identity-by-descent mapping in case-control studies

Identity-by-descent (IBD) mapping tests whether cases share more segments of IBD around a putative causal variant than do controls. These segments of IBD can be accurately detected from genome-wide SNP data. We investigate the power of IBD mapping relative to that of SNP association testing for genome-wide case-control SNP data. Our focus is particularly on rare variants, as these tend to be more recent and hence more likely to have recent shared ancestry. We simulate data from both large and small populations and find that the relative performance of IBD mapping and SNP association testing depends on population demographic history and the strength of selection against causal variants. We also present an IBD mapping analysis of a type 1 diabetes data set. In those data we find that we can detect association only with the HLA region using IBD mapping. Overall, our results suggest that IBD mapping may have higher power than association analysis of SNP data when multiple rare causal variants are clustered within a gene. However, for outbred populations, very large sample sizes may be required for genome-wide significance unless the causal variants have strong effects.

Performance of genotype imputation for rare variants identified in exons and flanking regions of genes

Genotype imputation has the potential to assess human genetic variation at a lower cost than assaying the variants using laboratory techniques. The performance of imputation for rare variants has not been comprehensively studied. We utilized 8865 human samples with high depth resequencing data for the exons and flanking regions of 202 genes and Genome-Wide Association Study (GWAS) data to characterize the performance of genotype imputation for rare variants. We evaluated reference sets ranging from 100 to 3713 subjects for imputing into samples typed for the Affymetrix (500K and 6.0) and Illumina 550K GWAS panels. The proportion of variants that could be well imputed (true r(2)>0.7) with a reference panel of 3713 individuals was: 31% (Illumina 550K) or 25% (Affymetrix 500K) with MAF (Minor Allele Frequency) less than or equal 0.001, 48% or 35% with 0.0010.05. The performance for common SNPs (MAF>0.05) within exons and flanking regions is comparable to imputation of more uniformly distributed SNPs. The performance for rare SNPs (0.01 Collapse

Key Words Collapse

MESH Headings

• Exons/genetics
• Gene Frequency
• Genes/genetics
• Genetic Variation
• Genome-Wide Association Study
• Genotype
• Humans
• Polymorphism, Single Nucleotide/genetics

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Grants

• R01 HG004960 NHGRI NIH HHS
• R01 HG005701 NHGRI NIH HHS
• R01HG005701 NHGRI NIH HHS
• R01HG004960 NHGRI NIH HHS

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Affiliation(s)

Li Li Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Yun Li Department of Genetics, Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
Sharon R. Browning Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
Brian L. Browning Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington, United States of America
Andrew J. Slater Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Xiangyang Kong Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Jennifer L. Aponte Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Vincent E. Mooser Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Stephanie L. Chissoe Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
John C. Whittaker Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Matthew R. Nelson Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom
Margaret Gelder Ehm Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America, King of Prussia, Pennsylvania, United States of America, and Stevenage, United Kingdom

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Genome-wide association study on bipolar disorder in the Bulgarian population

Bipolar disorder is a severe psychiatric disorder influenced by environmental and genetic factors. Genetic studies have implicated many variants in the disease's etiology but only few have been successfully replicated. We conducted a genome-wide association study (GWAS) on bipolar disorder in the Bulgarian population followed by a replication study of the top 100 single nucleotide polymorphisms (SNPs) showing the smallest P values. The GWAS was performed on 188 bipolar disorder patients and 376 control subjects genotyped on the Illumina 550 platform. The replication study was conducted on 122 patients and 328 controls. Although our study did not show any association P value that achieved genome-wide significance, and none of the top 100 SNPs reached the Bonferroni-corrected P value in the replication study, the plausible involvement of some variants cannot be entirely discarded. Three polymorphisms, rs8099939 [P = 2.12 × 10(-6), odds ratio (OR) = 1.95, 95% confidence interval (CI) = 1.43-2.67] in GRIK5, rs6122972 (P = 3.11 × 10(-6), OR = 2.02, 95% CI = 1.46-2.80) in PARD6B and rs2289700 (P = 9.14 × 10(-6), OR = 2.13, 95% CI = 1.53-2.95) in CTSH remained associated at a similar level after Mantel-Haenszel test for combining the results from the genome-wide and replication studies. A modest association was also detected for SNP rs1012053 (GWAS P = 4.50 × 10(-2)) in DGKH, which has already been reported as the most significant variant in a previous genome-wide scan on bipolar disorder. However, further studies using larger datasets are needed to identify variants with smaller effects that contribute to the risk of bipolar disorder.

Identification of genetic loci underlying the phenotypic constructs of autism spectrum disorders

OBJECTIVE

To investigate the underlying phenotypic constructs in autism spectrum disorders (ASD) and to identify genetic loci that are linked to these empirically derived factors.

METHOD

Exploratory factor analysis was applied to two datasets with 28 selected Autism Diagnostic Interview-Revised (ADI-R) algorithm items. The first dataset was from the Autism Genome Project (AGP) phase I (1,236 ASD subjects from 618 families); the second was from the AGP phase II (804 unrelated ASD subjects). Variables derived from the factor analysis were then used as quantitative traits in genome-wide variance components linkage analyses.

RESULTS

Six factors, namely, joint attention, social interaction and communication, nonverbal communication, repetitive sensory-motor behavior, peer interaction, and compulsion/restricted interests, were retained for both datasets. There was good agreement between the factor loading patterns from the two datasets. All factors showed familial aggregation. Suggestive evidence for linkage was obtained for the joint attention factor on 11q23. Genome-wide significant evidence for linkage was obtained for the repetitive sensory-motor behavior factor on 19q13.3.

CONCLUSIONS

This study demonstrates that the underlying phenotypic constructs based on the ADI-R algorithm items are replicable in independent datasets, and that the empirically derived factors are suitable and informative in genetic studies of ASD.

Comparative linkage meta-analysis reveals regionally-distinct, disparate genetic architectures: application to bipolar disorder and schizophrenia

New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for ”missing heritability.” However, the optimal analytic strategies for approaching such data are still actively debated, representing the latest rate-limiting step in genetic progress. Since it is likely a majority of common variants of modest effect have been identified through the application of tagSNP-based microarray platforms (i.e., GWAS), alternative approaches robust to detection of low-frequency (1–5% MAF) and rare (<1%) variants are of great importance. Of direct relevance, we have available an accumulated wealth of linkage data collected through traditional genetic methods over several decades, the full value of which has not been exhausted. To that end, we compare results from two different linkage meta-analysis methods—GSMA and MSP—applied to the same set of 13 bipolar disorder and 16 schizophrenia GWLS datasets. Interestingly, we find that the two methods implicate distinct, largely non-overlapping, genomic regions. Furthermore, based on the statistical methods themselves and our contextualization of these results within the larger genetic literatures, our findings suggest, for each disorder, distinct genetic architectures may reside within disparate genomic regions. Thus, comparative linkage meta-analysis (CLMA) may be used to optimize low-frequency and rare variant discovery in the modern genomic era.

Genome-wide association study of recurrent major depressive disorder in two European case-control cohorts

Major depressive disorder (MDD) is a highly prevalent disorder with substantial heritability. Heritability has been shown to be substantial and higher in the variant of MDD characterized by recurrent episodes of depression. Genetic studies have thus far failed to identify clear and consistent evidence of genetic risk factors for MDD. We conducted a genome-wide association study (GWAS) in two independent datasets. The first GWAS was performed on 1022 recurrent MDD patients and 1000 controls genotyped on the Illumina 550 platform. The second was conducted on 492 recurrent MDD patients and 1052 controls selected from a population-based collection, genotyped on the Affymetrix 5.0 platform. Neither GWAS identified any SNP that achieved GWAS significance. We obtained imputed genotypes at the Illumina loci for the individuals genotyped on the Affymetrix platform, and performed a meta-analysis of the two GWASs for this common set of approximately half a million SNPs. The meta-analysis did not yield genome-wide significant results either. The results from our study suggest that SNPs with substantial odds ratio are unlikely to exist for MDD, at least in our datasets and among the relatively common SNPs genotyped or tagged by the half-million-loci arrays. Meta-analysis of larger datasets is warranted to identify SNPs with smaller effects or with rarer allele frequencies that contribute to the risk of MDD.

Interpretation of association signals and identification of causal variants from genome-wide association studies

GWAS have been successful in identifying disease susceptibility loci, but it remains a challenge to pinpoint the causal variants in subsequent fine-mapping studies. A conventional fine-mapping effort starts by sequencing dozens of randomly selected samples at susceptibility loci to discover candidate variants, which are then placed on custom arrays or used in imputation algorithms to find the causal variants. We propose that one or several rare or low-frequency causal variants can hitchhike the same common tag SNP, so causal variants may not be easily unveiled by conventional efforts. Here, we first demonstrate that the true effect size and proportion of variance explained by a collection of rare causal variants can be underestimated by a common tag SNP, thereby accounting for some of the "missing heritability" in GWAS. We then describe a case-selection approach based on phasing long-range haplotypes and sequencing cases predicted to harbor causal variants. We compare this approach with conventional strategies on a simulated data set, and we demonstrate its advantages when multiple causal variants are present. We also evaluate this approach in a GWAS on hearing loss, where the most common causal variant has a minor allele frequency (MAF) of 1.3% in the general population and 8.2% in 329 cases. With our case-selection approach, it is present in 88% of the 32 selected cases (MAF = 66%), so sequencing a subset of these cases can readily reveal the causal allele. Our results suggest that thinking beyond common variants is essential in interpreting GWAS signals and identifying causal variants.

Beyond categorical diagnostics in psychiatry: Scientific and medicolegal implications

Conforming to a medical disease model rooted in phenomenology and natural science, psychiatry classifies mental disorders according to signs and symptoms considered to be stable and homogeneous across individuals. Scientific studies addressing the validity of this classification are scarce. Following a seminal paper by Robins and Guze in 1970, validity of categories has been sought in specific criteria referring to symptoms and prognosis, aggregation in families, and "markers", preferentially laboratory tests. There is, however, a growing misfit between the model and empirical findings from studies putting it to the test. Diagnostic categories have not been shown to represent natural groups delineated from the normal variation or from each other. Aetiological factors (genetic and/or environmental), laboratory aberrations, and treatment effects do not respect categorical boundaries. A more adequate description of mental problems may be achieved by: 1) a clear definition of the epistemological frame in which psychiatry operates, 2) a basic rating of the severity of intra- and interpersonal dysfunctions, and 3) empirical comparisons to complementary rather than exclusive dimensions of inter-individual differences in context-specific mental functions, treatment effects, and laboratory findings. Such a pluralistic understanding of mental health problems would fit empirical models in the neurosciences and postmodern notions of subjectivity alike. It would also clarify the assessment of dysfunction and background factors in relation to the requisites for penal law exemptions or insurance policies and make them empirically testable rather than dependent on expert opinion on issues such as whether a specific dysfunction is "psychiatric", "medical", or ascribable to "personality".

Methodological issues in molecular genetic studies of mental disorders

The development of methodologies for assaying genetic variation at high resolution throughout the genome has revolutionized the search for susceptibility genes for common diseases. This search, however, has been less successful in psychiatry than in other areas of medicine. It is hypothesized that the imprecision and uncertain validity of psychiatric diagnoses are major factors in this disappointing progress. Here we discuss the methodologies employed for genetic investigation of mental disorders, including phenotyping strategies, approaches to genetic mapping, and use of animal models of psychopathology.