Genome-wide scan in 124 Indonesian sib-pair families with schizophrenia reveals genome-wide significant linkage to a locus on chromosome 3p26-21

Association between genetic variants of GRM7 (rs1396409 and rs9883258) and treatment outcomes in Schizophrenic Egyptian patients

BACKGROUND AND AIM

This study evaluated the association between rs1396409 and rs9883258 and the risk of schizophrenia (SCZ) and treatment outcomes in Egyptian patients.

METHODS

This study included 88 patients with SCZ and 88 healthy controls. Lipid profile was assayed. Genotyping of rs1396409 and rs9883258 polymorphisms was analyzed using real-time PCR.

RESULTS

The rs1396409 AG genotype frequency was significantly associated with SCZ risk (p = 0.002). Also, significant increased risk of SCZ was observed under allelic (p = 0.001), dominant (p = 0.001) and overdominant (p = 0.001) genetic model of rs1396409. However, rs9883258 AA genotype revealed nonsignificant association with SCZ. Cases with the rs1396409AG genotype exhibited hypertriglyceridemia (p < 0.001) and hypercholesterolemia (p = 0.001). In total, 72.3% and 74.5% of the cases presented with rs1396409 AG have negative symptoms (p = 0.022) and exhibited poor drug response (p = 0.023), respectively; all cases with rs1396409 GG genotype attempted suicide (p = 0.002) and are drug-free (p = 0.003). SCZ patients with negative symptoms had hypercholesterolemia (p = 0.008) mainly low-density lipoproteins (LDLc) (p = 0.016), and those with cognitive symptoms presented with low level of high-density lipoprotein (HDLc) (p = 0.023). Moreover, the multivariate regression analysis revealed that both rs1396409 G allele and HDLc were predictors of SCZ (p = 0.003 and 0.001, resp.).

CONCLUSION

The current study concluded that metabotropic glutamate receptor 7 (GRM7) rs1396409 AG could be a potential biomarker for SCZ diagnosis. It also revealed an independent association between the GRM7 rs1396409 G allele, HDLc and SCZ development.

GRM7 polymorphisms and risk of schizophrenia in Iranian population

The role of metabotropic glutamate receptors in the pathogenesis of schizophrenia or response to antipsychotic treatment has been proposed previously. The aim of the current study was to investigate the associations between two intronic variants within GRM7 gene (rs6782011 and rs779867) and schizophrenia in Iranian population. These two single nucleotide polymorphisms (SNPs) were genotyped in 273 schizophrenic patients and 300 age and sex-matched normal controls. The frequency of A allele of the rs779867 was significantly lower in the schizophrenic patients compared with healthy subjects (OR (95% CI) = 0.71 (0.56-0.89), adjusted P value = 0.008). This SNP was associated with schizophrenia in co-dominant and dominant models (adjusted P values of 0.03 and 0.02 respectively). However, there was no difference in allele and genotype frequencies of the rs6782011 SNP between cases and controls. Consequently, the results of current study further highlight the participation of GRM7 in the pathogenesis of schizophrenia.

A systematic review of genome-wide association studies of antipsychotic response

Clinical symptom response to antipsychotic medications is highly variable. Genome-wide association studies (GWAS) provide a 'hypothesis-free' method of interrogating the genome for biomarkers of antipsychotic response. We performed a systematic review of GWAS findings for antipsychotic efficacy or effectiveness. 14 studies met our inclusion criteria, ten of which examined antipsychotic response using quantitative rating scales to measure symptom improvement. 15 genome-wide significant loci were identified, seven of which were replicated in other antipsychotic GWAS publications: CNTNAP5, GRID2, GRM7, 8q24 (KCNK9), PCDH7, SLC1A1 and TNIK. Notably, four replicated loci are involved in glutamatergic pathways. Additional validation and evaluation of the biological significance of these markers is warranted. These markers should also be evaluated for clinical utility, especially in the context of other validated pharmacogenomic variants (e.g., CYP450 genes). These findings may generate new avenues for development of novel antipsychotic treatments.

Association of the type 2 diabetes mellitus susceptibility gene, TCF7L2, with schizophrenia in an Arab-Israeli family sample

Many reports in different populations have demonstrated linkage of the 10q24-q26 region to schizophrenia, thus encouraging further analysis of this locus for detection of specific schizophrenia genes. Our group previously reported linkage of the 10q24-q26 region to schizophrenia in a unique, homogeneous sample of Arab-Israeli families with multiple schizophrenia-affected individuals, under a dominant model of inheritance. To further explore this candidate region and identify specific susceptibility variants within it, we performed re-analysis of the 10q24-26 genotype data, taken from our previous genome-wide association study (GWAS) (Alkelai et al, 2011). We analyzed 2089 SNPs in an extended sample of 57 Arab Israeli families (189 genotyped individuals), under the dominant model of inheritance, which best fits this locus according to previously performed MOD score analysis. We found significant association with schizophrenia of the TCF7L2 gene intronic SNP, rs12573128, (p = 7.01×10⁻⁶) and of the nearby intergenic SNP, rs1033772, (p = 6.59×10⁻⁶) which is positioned between TCF7L2 and HABP2. TCF7L2 is one of the best confirmed susceptibility genes for type 2 diabetes (T2D) among different ethnic groups, has a role in pancreatic beta cell function and may contribute to the comorbidity of schizophrenia and T2D. These preliminary results independently support previous findings regarding a possible role of TCF7L2 in susceptibility to schizophrenia, and strengthen the importance of integrating linkage analysis models of inheritance while performing association analyses in regions of interest. Further validation studies in additional populations are required.

Using multivariate machine learning methods and structural MRI to classify childhood onset schizophrenia and healthy controls

INTRODUCTION

Multivariate machine learning methods can be used to classify groups of schizophrenia patients and controls using structural magnetic resonance imaging (MRI). However, machine learning methods to date have not been extended beyond classification and contemporaneously applied in a meaningful way to clinical measures. We hypothesized that brain measures would classify groups, and that increased likelihood of being classified as a patient using regional brain measures would be positively related to illness severity, developmental delays, and genetic risk.

METHODS

Using 74 anatomic brain MRI sub regions and Random Forest (RF), a machine learning method, we classified 98 childhood onset schizophrenia (COS) patients and 99 age, sex, and ethnicity-matched healthy controls. We also used RF to estimate the probability of being classified as a schizophrenia patient based on MRI measures. We then explored relationships between brain-based probability of illness and symptoms, premorbid development, and presence of copy number variation (CNV) associated with schizophrenia.

RESULTS

Brain regions jointly classified COS and control groups with 73.7% accuracy. Greater brain-based probability of illness was associated with worse functioning (p = 0.0004) and fewer developmental delays (p = 0.02). Presence of CNV was associated with lower probability of being classified as schizophrenia (p = 0.001). The regions that were most important in classifying groups included left temporal lobes, bilateral dorsolateral prefrontal regions, and left medial parietal lobes.

CONCLUSION

Schizophrenia and control groups can be well classified using RF and anatomic brain measures, and brain-based probability of illness has a positive relationship with illness severity and a negative relationship with developmental delays/problems and CNV-based risk.

A Novel Microduplication in the Neurodevelopmental Gene SRGAP3 That Segregates with Psychotic Illness in the Family of a COS Proband

Schizophrenia is a debilitating mental disorder affecting approximately 1% of the world's population. Childhood onset schizophrenia (COS), defined as onset before age 13, is a rare and severe form of the illness that may have more salient genetic influence. We identified a ~134 kb duplication spanning exons 2–4 of the Slit-Robo GTPase-activating protein 3 (SRGAP3) gene on chromosome 3p25.3 that tracks with psychotic illness in the family of a COS proband. Cloning and sequencing of the duplication junction confirmed that the duplication is tandem, and analysis of the resulting mRNA transcript suggests that the duplication would result in a frame shift mutation. This is the first family report of a SRGAP3 copy number variant (CNV) in schizophrenia. Considering that SRGAP3 is important in neural development, we conclude that this SRGAP3 duplication may be an important factor contributing to the psychotic phenotype in this family.

Family-based designs for genome-wide association studies

Association mapping has successfully identified common SNPs associated with many diseases. However, the inability of this class of variation to account for most of the supposed heritability has led to a renewed interest in methods - primarily linkage analysis - to detect rare variants. Family designs allow for control of population stratification, investigations of questions such as parent-of-origin effects and other applications that are imperfectly or not readily addressed in case-control association studies. This article guides readers through the interface between linkage and association analysis, reviews the new methodologies and provides useful guidelines for applications. Just as effective SNP-genotyping tools helped to realize the potential of association studies, next-generation sequencing tools will benefit genetic studies by improving the power of family-based approaches.

Polymorphisms of XRCC4 are involved in reduced colorectal cancer risk in Chinese schizophrenia patients

Background

Genetic factors related to the regulation of apoptosis in schizophrenia patients may be involved in a reduced vulnerability to cancer. XRCC4 is one of the potential candidate genes associated with schizophrenia which might induce colorectal cancer resistance.

Methods

To examine the genetic association between colorectal cancer and schizophrenia, we analyzed five SNPs (rs6452526, rs2662238, rs963248, rs35268, rs2386275) covering ~205.7 kb in the region of XRCC4.

Results

We observed that two of the five genetic polymorphisms showed statistically significant differences between 312 colorectal cancer subjects without schizophrenia and 270 schizophrenia subjects (rs6452536, p = 0.004, OR 0.61, 95% CI 0.44-0.86; rs35268, p = 0.028, OR 1.54, 95% CI 1.05-2.26). Moreover, the haplotype which combined all five markers was the most significant, giving a global p = 0.0005.

Conclusions

Our data firstly indicate that XRCC4 may be a potential protective gene towards schizophrenia, conferring reduced susceptibility to colorectal cancer in the Han Chinese population.

A family-based association study of DNA sequence variants in GRM7 with schizophrenia in an Indonesian population

We previously reported genome-wide significant linkage to chromosome 3p in a sib-pair family sample from Indonesia. A promising candidate gene within the linked region is the metabotropic glutamate receptor subtype 7 (GRM7), involved in glutamatergic neurotransmission. We genotyped 18 single nucleotide polymorphisms in GRM7 in the sample of 124 Indonesian sib-pair families that had provided the significant linkage finding. Transmission disequilibrium analysis revealed nominally significant transmission distortion of rs17031835 in intron 1 of GRM7 (p=0.004, before correction for multiple testing), along with haplotypes containing rs17031835. No other single marker was found to be significantly associated with schizophrenia in our sample. The results from our study provide support for the idea that glutamatergic neurotransmission and specifically the GRM7 gene might be relevant to the development of schizophrenia. Further studies supporting this finding are warranted.

Meta-analysis of 32 genome-wide linkage studies of schizophrenia

A genome scan meta-analysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (P(SR)) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142-168 Mb) and 2q (103-134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119-152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for 'aggregate' genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16-33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies.

Genome-wide association studies in ADHD

Attention-deficit/hyperactivity disorder, ADHD, is a common and highly heritable neuropsychiatric disorder that is seen in children and adults. Although heritability is estimated at around 76%, it has been hard to find genes underlying the disorder. ADHD is a multifactorial disorder, in which many genes, all with a small effect, are thought to cause the disorder in the presence of unfavorable environmental conditions. Whole genome linkage analyses have not yet lead to the identification of genes for ADHD, and results of candidate gene-based association studies have been able to explain only a tiny part of the genetic contribution to disease, either. A novel way of performing hypothesis-free analysis of the genome suitable for the identification of disease risk genes of considerably smaller effect is the genome-wide association study (GWAS). So far, five GWAS have been performed on the diagnosis of ADHD and related phenotypes. Four of these are based on a sample set of 958 parent-child trio's collected as part of the International Multicentre ADHD Genetics (IMAGE) study and genotyped with funds from the Genetic Association Information Network (GAIN). The other is a pooled GWAS including adult patients with ADHD and controls. None of the papers reports any associations that are formally genome-wide significant after correction for multiple testing. There is also very limited overlap between studies, apart from an association with CDH13, which is reported in three of the studies. Little evidence supports an important role for the 'classic' ADHD genes, with possible exceptions for SLC9A9, NOS1 and CNR1. There is extensive overlap with findings from other psychiatric disorders. Though not genome-wide significant, findings from the individual studies converge to paint an interesting picture: whereas little evidence-as yet-points to a direct involvement of neurotransmitters (at least the classic dopaminergic, noradrenergic and serotonergic pathways) or regulators of neurotransmission, some suggestions are found for involvement of 'new' neurotransmission and cell-cell communication systems. A potential involvement of potassium channel subunits and regulators warrants further investigation. More basic processes also seem involved in ADHD, like cell division, adhesion (especially via cadherin and integrin systems), neuronal migration, and neuronal plasticity, as well as related transcription, cell polarity and extracellular matrix regulation, and cytoskeletal remodeling processes. In conclusion, the GWAS performed so far in ADHD, though far from conclusive, provide a first glimpse at genes for the disorder. Many more (much larger studies) will be needed. For this, collaboration between researchers as well as standardized protocols for phenotyping and DNA-collection will become increasingly important.