In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding.

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Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant inter-population pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective.

BackgroundThe association of the deletion in GSTT1 and GSTM1 genes with coronary artery disease (CAD) among smokers is controversial. In addition, no such investigation has previously been conducted among Arabs.MethodsWe genotyped 1054 CAD patients and 762 controls for GSTT1 and GSTM1 deletion by multiplex polymerase chain reaction. Both CAD and controls were Saudi Arabs.ResultsIn the control group (n = 762), 82.3% had the T wild M wildgenotype, 9% had the Twild M null, 2.4% had the Tnull M wild and 6.3% had the Tnull M null genotype. Among the CAD group (n = 1054), 29.5% had the Twild M wild genotype, 26.6% (p < .001) had the Twild M null, 8.3% (p < .001) had the Tnull M wild and 35.6% (p < .001) had the Tnull M null genotype, indicating a significant association of the Twild M null, Tnull M wild and Tnull M null genotypes with CAD. Univariate analysis also showed that smoking, age, hypercholesterolemia and hypertriglyceridemia, diabetes mellitus, family history of CAD, hypertension and obesity are all associated with CAD, whereas gender and myocardial infarction are not. Binary logistic regression for smoking and genotypes indicated that only M null and Tnullare interacting with smoking. However, further subgroup analysis stratifying the data by smoking status suggested that genotype-smoking interactions have no effect on the development of CAD.ConclusionGSTT1 and GSTM1 null-genotypes are risk factor for CAD independent of genotype-smoking interaction.

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