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Challenges in identifying genetic risk factors for common multifactorial disorders.

Advances in recombinant DNA technology have opened up many new diagnostic tools for monogenic disorders. DNA based techniques are also being used in the diagnosis of infectious diseases, and diagnosis and prognostication of cancers. Research in molecular pathogenesis of these disorders is likely to bring up new therapeutic strategies. The monogenic disorders account for a small part of mortality and morbidity in the general population, which is mainly contributed by complex multifactorial disorders like diabetes, hypertension, coronary artery disease, etc. Hence currently major research is directed towards identification of genetic risk factors for these common diseases. The aims are to develop diagnostic tests to identify the individuals at high risk and to develop novel preventive and therapeutic strategies. In spite of very good molecular, computational and statistical tools, the efforts in this direction have till date not been very fruitful.

Most of the genetic risks for common disease must be conferred by low frequency alleles. (1) Most of these factors account for a small proportion of the total risk and their presence or absence will rarely increase or reduce recurrence risk of the relevant disorder more than two-fold. Thus, their diagnostic value is negligible. The most commonly used method to identify genetic risk factors for multifactorial disorders is association study which compares prevalence of a genotype in a group of patients with the disease in concern with that in the control population. When one reviews the literature over the last decade, it is seen that the genome wide association studies have often yielded contradictory results. Though billions of dollars have been spent to identify DNA variants in human genome that are more common in patients with a specific complex disease than in healthy individuals, the search for identification of major risk factors for complex disorders have remained elusive (1). Success is visible recently in exceptional situations like age related macular degeneration (2). Most association studies fail to identify the risk conferring allele not only due to insufficient sample size; but heterogeneity of the complex disorders (1). Polymorphisms in many genes interact with multiple known and unknown environmental factors ultimately resulting in the disease phenotype. It means that in each family and in each individual the contribution of various genetic variations to the disease phenotype may vary, and different combinations of different genetic variations may give rise to the similar phenotypes. Hence to get consistent and statistically significant results of association studies is difficult. This is obvious from the various studies of methylene tetrahydrofolate reductase (MTHFR) gene polymorphism in coronary artery disease and other thrombotic disorders.

Rassoul et al (3) in this issue have studied plasma homocysteine level and 677 C[right arrow]T polymorphism in MTHFR gene in patients with coronary artery disease (CAD) and concluded that the serum homocysteine level was associated with severity of CAD, but MTHFR polymorphism did not affect the severity of CAD (3). There are other studies on hyperhomocysteinemia and MTHFR polymorphism in atherosclerosis and coronary artery disease (4,5). The association between CAD and MTHFR polymorphism has been noted a decade ago (6). Homozygosity for the C677T mutation in the MTHFR gene is commonly but inconsistently associated with hyperhomocysteinemia. MTHFR catalyzes the conversion of methylenetetrahydrofolate to methyltetrahydrofolate, the methyl donor in the remethylation of homocysteine to methionine. A 677C[right arrow]T mutation in the MTHFR gene has been associated with elevated homocysteine concentrations in homozygous individuals as this change in nucleotide is known to reduce enzymatic activity of MTHFR. Hyperhomocysteinemia is an accepted risk factor for coronary artery disease, but the determining factors are not fully understood. It may result from both environmental and hereditary factors. Other genes may also be influencing plasma homocysteine levels (7). Environmental factors like diet, alcohol also affect the serum homocysteine level (8).

Though it has been presumed that MTHFR polymorphism 677C [right arrow] T acts through hyperhomocysteinemia; there have been studies to show that these may have combinational effect. Mager et al (9) have reported that hyperhomocysteinemia and the T/T genotype had a stronger effect on the pathogenesis of CAD when they are combined, and that a marked increase (> 15 [micro]mol/l) in fasting plasma homocysteine in T/T homozygotes was a risk factor for early onset of CAD.

There are many studies refuting the association of common polymorphism in MTHFR gene and CAD (10-17). Brilakis et a1 (16) reported that the MTHFR TT genotype was associated with hyperhomocysteinemia, but not with significant CAD. A large case control study of more than 2000 patients with CAD has not shown association between MTHFR C677T and A1298C polymorphisms (18). In the analysis of the 12 studies, the odds ratio of CAD associated with the TT genotype (homozygous C677T polymorphism) was 1.18 (19). The meta-analysis showed a slightly higher plasma homocysteine levels in participants with the TT genotype vs. CC and CT genotypes. Another meta-analysis also concluded that although the C677T/MTHFR mutation is a major cause of mild hyperhomocysteinemia, does not increase cardiovascular risk (20).

In addition to MTHFR C677T polymorphism, other polymorphisms in MTHFR and other genes in the pathway, namely, methionine synthase (MTR), cystathionine-beta-synthase and methionine synthase reductase (MTRR) are being studied knowing the polygenic aetiology of hypermethionemia and CAD (21,22). The contribution to total plasma homocysteine levels of the common mutations of genes coding for the enzymes controlling homocysteine metabolism appears to be modest (23).

Indian groups have also studied association of MTHFR 677C [right arrow] T with CAD. Alam et al have shown that hyperhomocysteinemia appears to have a graded effect on the risk of CAD as well as the severity and extent of coronary atherosclerosis (24). This study has also shown that homozygous genotype of MTHFR is a genetic risk factor for CAD in Indian population. On the other hand, a study by Mukherjee et al (25) has failed to show the association of MTHFR C677T polymorphism in Indian patients with CAD. Studies done to see association of the polymorphism with restenosis showed conflicting results (26,27).

These studies bring Out the difficulty in concluding about small contribution of a genetic polymorphism to a multifactorial disease. If MTHFR 677C [right arrow] T is a risk factor for CAD, it had a modest effect. Probably, the homozygous T/T genotype is a modest but significant risk factor for CAD at least in some populations. However, this risk factor may be of great importance as hyperhomocysteinemia because of the C677T MTHFR allele may be corrected with oral folic acid therapy (28). Kauwell et a1 (29) showed that TT homozygotes on low folate diet had higher rise in plasma homocysteine level as compared to heterozygotes on low folate diet and the levels of plasma homocysteine returned to normal on repletion of folate in the diet. Thus, it is important to know whether MTHFR 677C [right arrow] T polymorphism is a risk factor for at least some cases of CAD. It has been realized that CAD is an important public health issue in India and further investigations on the relationships between MTHFR genotypes and the incidence of CAD based on larger samples are necessary. Array based single nucleotide polymorphism (SNP) typing (more than 500,000 SNPs are studied in one experiment) and analysis of large cohorts of patients have significantly enhanced the power of association studies and have identified risk factors for myocardial infarction (30,31). Individual therapeutic strategies based on single nucleotide polymorphism may become increasingly important for preventive treatment against polygenic CAD.

Shubha R. Phadke

Department of Medical Genetics

Sanjay Gandhi Post Graduate Institute of

Medical Sciences

Lucknow 226 014, India

shubha@sgpgi.ac.in

References

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Title Annotation:Commentary
Author:Phadke, Shubha R.
Publication:Indian Journal of Medical Research
Article Type:Report
Geographic Code:9INDI
Date:Feb 1, 2008
Words:2372
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