POSTER NO: 678

Single Nucleotide Polymorphisms in GABA_A receptor genes identified through two different approaches, and analysis for their association with schizophrenia

Carol Lau
Department of Biochemistry, HK University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China

With human genome sequence available, focus is now on the genome variation. The most common is Single Nucleotide Polymorphisms (SNPs). There are about 1.42 million SNPs distributed throughout the genome. It is a single base pair positions in genomic DNA at which different sequence alternatives exist in population. Many complex diseases may arise from quantitative rather than qualitative, differences in gene products. Therefore, by comparing patterns and frequencies of SNPs in patients and controls, it is possible to identify which SNPs are associated with which diseases.

Schizophrenia is a common psychiatric disease that has about 1% population prevalence. According to the family, twin, and adoption studies, there are at least 65-85% of genetic factors for the risk to develop schizophrenia. However, the etiopathogenesis of schizophrenia has not yet been revealed. Some reported association between susceptibility to schizophrenia and gamma-Aminobutyric acid receptor (GABA receptor) are based on comparing the change in GABA quantity, subunit expression, or studying dinucleotide repeat marker between schizophrenic patients and normal controls. Therefore, other than dopamine receptor, GABA receptor may be susceptible gene of schizophrenia.

This research is to study SNPs in Human GABA_A Receptor by two identification approaches - experimental sequencing and ESTs alignment, and analysis of their association with schizophrenia. The first approach is the experimental sequencing. Forty-six normal subject as controls and forty-six schizophrenic patients samples from Chinese population were used. Ten SNPs were identified in four subunit genes in human GABA_A receptor. Among these SNPs, three of them are non-synonymous cSNPs and only two appear to be of marginal significance to schizophrenia. The non-coding SNP identified in one subunit gene and the non-synonymous SNP identified in another subunit gene both gave p values equal to 0.05, which are marginally significant.

The second approach is ESTs alignment. Seven candidate SNPs were predicted, four of these are available in the dbSNP in NCBI. However, only two of these were verified as SNPs by experimentation. For this approach, twenty samples were used, so the experimental sequencing can verify SNPs that have an occurrence frequency greater than 5%.

In conclusion, Experimental sequencing is a common approach in SNPs identification. It is relatively accurate but time consuming and expensive. From this approach, two SNPs in GABA_A receptor were found to be marginally significant to schizophrenia. Therefore, further studies will continue to investigate these two SNPs by increasing sample size. In comparison, the second approach can readily predict potential SNPs from public databases. However, from the above results, it is clear that these predicted SNPs must be verified through experimental methods in order to rule out EST-sequencing errors.