Genomics companies, health risks, and personalized health interventions... can they really say much?

..basically, we're still years away from being able to tell people about their health risks or about how they should eat/behave based on their genetic information. The authors of this paper (in AJHG, see abstract below) look in published meta analyses to assess the strength of the evidence for associations between the polymorphisms that companies test and disease risk. I wish they would have discussed some of the more promising gene-disease associations, and talked about what we can learn from those cases.

the companies they looked at (I've never heard of any of them):

... identified seven companies that offer predictive genetic testing using multiple markers (Genelex, Genovations,Genosolutions, Integrative Genomics, Salugen, Scionaand Suracell).

what these companies test:

The seven companies tested at least 69 different polymorphismsin 56 genes (Table S1). Only one gene (MTHFR [MIM 07093]) was tested by all seven companies, seven genes (CETP [MIM 118470], COL1A1 [MIM 120150], GSTM1 [MIM 138350], GSTP1 [MIM 134660], IL-6 [MIM
147620], TNF-a [MIM 191160], and VDR [MIM 601769])were tested by five or six companies, and 19 genes (34%) were tested by only one company.

what the published meta analyses of the genes shows:

Of the 160 unique polymorphism-disease associations that had been examined by meta-analysis, 60 were statistically significant (Figure 1 and Table S2), including significant associations for 29 of 69 polymorphisms in 25 (45%) of the 56 genes. However, statistically significant associations were generally modest, with significant odds ratios (ORs) ranging from 0.54 to 0.88 for protective allelesor genotypes and from 1.04 to 1.50 for risk alleles or genotypes,...

and:

On average, meta-analyses showed a significant association with disease risk for 58% of the genes included in each profile (range 38%–83%) (Table 1). These significant associations, however, were often with risk for disease outcomes other than those associated with the ‘‘profile’’

BUT:

The review did not assess the scientific basis of gene-expression profiles and pharmacogenomic applications. Although there may be applications that have stronger scientific support than others, there are clearly promising developments in this area.13,14

and,

Because the genetic profiles of the companies are offered to the general public, we restricted our search to meta-analyses of studies that included healthy or general-population controls. Because the predictive value of genetic testing depends on disease risk, genotype frequencies, and odds ratios for the association between disease risk and polymorphisms in a particular genetic profile, all of which may differ betweenpopulations, the profiles should be evaluated in the target population.15

about how single genes, like my favorite, MTHFR, can be associated with risk AND protective effects:

Furthermore, several genes, such as ACE [MIM 106180], APOE, and MTHFR, increase people’s risk for some diseases and decrease their risk for others (Table S2). For example, MTHFR 677TT was associated with an increased risk for depression, stroke, coronary artery disease, gastric cancer, schizophrenia, and venous thrombosis, but it was associated with a decreased risk for colorectal cancer. Hence, the putative health effects of preventive interventions tailored to a person’s MTHFR genotype may not be entirely beneficial.

A Critical Appraisal of the Scientific Basis of Commercial Genomic Profiles Used to Assess Health Risks and Personalize Health Interventions
A. Cecile J.W. Janssens, Marta Gwinn, Linda A. Bradley, Ben A. Oostra, Cornelia M. van Duijn and Muin J. Khoury
American Journal of Human Genetics, Volume 82, Issue 3, 593-599, 3 March 2008

Abstract: Predictive genomic profiling used to produce personalized nutrition and other lifestyle health recommendations is currently offered directly to consumers. By examining previous meta-analyses and HuGE reviews, we assessed the scientific evidence supporting the purported gene-disease associations for genes included in genomic profiles offered online. We identified seven companies that offer predictive genomic profiling. We searched PubMed for meta-analyses and HuGE reviews of studies of gene-disease associations published from 2000 through June 2007 in which the genotypes of people with a disease were compared with those of a healthy or general-population control group. The seven companies tested at least 69 different polymorphisms in 56 genes. Of the 56 genes tested, 24 (43%) were not reviewed in meta-analyses. For the remaining 32 genes, we found 260 meta-analyses that examined 160 unique polymorphism-disease associations, of which only 60 (38%) were found to be statistically significant. Even the 60 significant associations, which involved 29 different polymorphisms and 28 different diseases, were generally modest, with synthetic odds ratios ranging from 0.54 to 0.88 for protective variants and from 1.04 to 3.2 for risk variants. Furthermore, genes in cardiogenomic profiles were more frequently associated with noncardiovascular diseases than with cardiovascular diseases, and though two of the five genes of the osteogenomic profiles did show significant associations with disease, the associations were not with bone diseases. There is insufficient scientific evidence to conclude that genomic profiles are useful in measuring genetic risk for common diseases or in developing personalized diet and lifestyle recommendations for disease prevention.