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WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Patients with low tacrolimus troughs are at a higher risk of rejection while those with high troughs are at an increased risk for toxicity. Therefore, achieving the therapeutic range is important.• CYP3A5 genotype and days post transplant have been previously shown individually to be associated with tacrolimus troughs.WHAT THIS STUDY ADDS• This paper presents the first dosing model for tacrolimus using a combination of genetic and clinical factors in adult kidney transplant recipients. It was developed from one of the largest tacrolimus pharmacogenetic studies conducted to date (681 subjects and 11 823 trough concentrations).• We found that CL/F was significantly influenced by days post transplant, CYP3A5 genotype, transplantation at a steroid sparing centre, recipient age and the use of a calcium channel blocker.• Our large sample size enabled us to define the distinct differences in tacrolimus CL/F between three CYP3A5 genotype groups (*1/*1, *1/*3 and *3/*3).• This study is an important step towards using pharmacogenetic information in the clinical setting.AIM To develop a dosing equation for tacrolimus, using genetic and clinical factors from a large cohort of kidney transplant recipients. Clinical factors and six genetic variants were screened for importance towards tacrolimus clearance (CL/F).METHODS Clinical data, tacrolimus troughs and corresponding doses were collected from 681 kidney transplant recipients in a multicentre observational study in the USA and Canada for the first 6 months post transplant. The patients were genotyped for 2 724 single nucleotide polymorphisms using a customized Affymetrix SNP chip. Clinical factors and the most important SNPs (rs776746, rs12114000, rs3734354, rs4926, rs3135506 and rs2608555) were analysed for their influence on tacrolimus CL/F.RESULTS The CYP3A5*1 genotype, days post transplant, age, transplant at a steroid sparing centre and calcium channel blocker (CCB) use significantly influenced tacrolimus CL/F. The final model describing CL/F (l h−1) was: 38.4 ×[(0.86, if days 6–10) or (0.71, if days 11–180)]×[(1.69, if CYP3A5*1/*3 genotype) or (2.00, if CYP3A5*1/*1 genotype)]× (0.70, if receiving a transplant at a steroid sparing centre) × ([age in years/50]−0.4) × (0.94, if CCB is present). The dose to achieve the desired trough is then prospectively determined using the individuals CL/F estimate.CONCLUSIONS The CYP3A5*1 genotype and four clinical factors were important for tacrolimus CL/F. An individualized dose is easily determined from the predicted CL/F. This study is important towards individualization of dosing in the clinical setting and may increase the number of patients achieving the target concentration. This equation requires validation in an independent cohort of kidney transplant recipients.

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The human genome contains frequent single-basepair variants that may or may not cause genetic disease. To characterize benign vs. pathogenic missense variants, numerous computational algorithms have been developed based on comparative sequence and/or protein structure analysis. We compared computational methods that use evolutionary conservation alone, amino acid (AA) change alone, and a combination of conservation and AA change in predicting the consequences of 254 missense variants in the CDKN2A (n = 92), MLH1 (n = 28), MSH2 (n = 14), MECP2 (n = 30), and tyrosinase (TYR) (n = 90) genes. Variants were validated as either neutral or deleterious by curated locus-specific mutation databases and published functional data. All methods that use evolutionary sequence analysis have comparable overall prediction accuracy (72.9-82.0%). Mutations at codons where the AA is absolutely conserved over a sufficient evolutionary distance (about one-third of variants) had a 91.6 to 96.8% likelihood of being deleterious. Three algorithms (SIFT, PolyPhen, and A-GVGD) that differentiate one variant from another at a given codon did not significantly improve predictive value over conservation score alone using the BLOSUM62 matrix. However, when all four methods were in agreement (62.7% of variants), predictive value improved to 88.1%. These results confirm a high predictive value for methods that use evolutionary sequence conservation, with or without considering protein structural change, to predict the clinical consequences of missense variants. The methods can be generalized across genes that cause different types of genetic disease. The results support the clinical use of computational methods as one tool to help interpret missense variants in genes associated with human genetic disease.

Background The CYP4503A5*1 genotype is associated with lower tacrolimus concentrations. Although its effect is important, it incompletely explains the variability in tacrolimus concentrations and has a relatively low minor allele frequency in Caucasians relative to African Americans (AA). Methods We studied clinical and recipient genetic correlates of dose-normalized tacrolimus troughs (n=12,277) in the first 6 months posttransplant using a customized single nucleotide polymorphism chip with 2,722 variants in a large, ethnically diverse (144 AA and 551 non-AA) adult kidney transplant population through a 7-center consortium. Results Over the 6 month study, AAs had consistently lower median (interquartile range) troughs than non-AAs, 6.2 (4.4–8.4) vs 8.3 (6.4–10.4) ng/mL (p<0.0001), in spite of 60% higher daily doses, 8 (5–10) vs 5 (4–7) mg (p<0.0001). The median tacrolimus trough concentration in week one posttransplant was particularly low in AAs [2.1 (1.2–3.5)] compared to non-AAs [5.0 (3.1–8.2) ng/mL](p<0.0001) despite similar initial doses. In single variant analysis, CYP3A5*3 (rs776746) was the top variant (p=2.4x10−33) associated with troughs. After adjustment for CYP3A5*3, clinical factors and race, thirty-nine additional variants were identified (p<0.01, not significant at FDR 20%). In the final multivariant, regression models beginning with these variants and clinical factors, 7 variants were identified in the non-AA and 7 variants in the AA group towards the first trough concentrations. Rs776746 (CYP3A5), rs2239393 (COMT) and diabetes were the only factors common in both populations. Conclusion We identified variants beyond CYP3A5*3 which may further explain pharmacokinetic variability of tacrolimus and demonstrated that important variants differ by race.

We report results from a genome wide association study (GWAS) of five quantitative indicators of behavioral disinhibition: Nicotine, Alcohol Consumption, Alcohol Dependence, Illicit Drugs, and non-substance related Behavioral Disinhibition. The sample, consisting of 7188 Caucasian individuals clustered in 2300 nuclear families, was genotyped on over 520,000 SNP markers from Illumina’s Human 660W-Quad Array. Analysis of individual SNP associations revealed only one marker-component phenotype association, between rs1868152 and Illicit Drugs, with a p-value below the standard genome-wide threshold of 5 × 10-8. Because we had analyzed five separate phenotypes, we do not consider this single association to be significant. However, we report 13 SNPs that were associated at p < 10-5 for one phenotype and p < 10-3 for at least one other phenotype, which are potential candidates for future investigations of variants associated with general behavioral disinhibition. Biometric analysis of the twin and family data yielded estimates of additive heritability for the component phenotypes ranging from 49% to 70%, GCTA estimates of heritability for the same phenotypes ranged from 8% to 37%. Consequently, even though the common variants genotyped on the GWAS array appear in aggregate to account for a sizable proportion of heritable effects in multiple indicators of behavioral disinhibition, our data suggest that most of the additive heritability remains “missing”.

Oculocutaneous albinism (OCA) is a common human genetic condition resulting from mutations in at least twelve different genes. OCA1 results from mutations of the tyrosinase gene and presents with the life-long absence of melanin pigment after birth (OCA1A) or with the development of minimal-to-moderate amounts of cutaneous and ocular pigment (OCA1B). Other types of OCA have variable amounts of cutaneous and ocular pigment. We hypothesized that white hair at birth indicates OCA1 and tested this in a sample of 120 probands with OCA and white hair at birth. We found that 102 (85%) of the probands had OCA1 with one or two identifiable tyrosinase gene mutations, with 169 (83%) of the 204 OCA1 tyrosinase gene alleles having identifiable mutations and 35 (17%) having no identifiable change in the coding, splice junction, or proximal promoter regions of the gene. The inability to identify the mutation was more common with OCA1B (24/35, 69%) than with OCA1A (11/35, 31%) alleles. Seven probands with no tyrosinase gene mutations were found to have OCA2 with one or two P gene mutations, and in eleven, no mutations were detected in either gene. We conclude that (1) the presence of white hair at birth is a useful clinical tool suggesting OCA1 in a child or adult with OCA, although OCA2 may also have this presentation; (2) the molecular analysis of the tyrosinase and P genes are necessary for precise diagnosis; and (3) the presence of alleles without identifiable mutations of the tyrosinase gene, particularly in OCA1B, suggests that more complex mutation mechanisms of this gene are common in OCA.

Through the last century there has been a steady progression provided insight into the biology of tyrosinase, including protein trafficking and structure/function analysis. Several in our understanding of the biology of melanin biosynthesis. Much of this work includes the analysis of coat color mutaquestions still remain, including cryptic mutations that affect tions of the mouse and albinism in man. Our understanding tyrosinase activity and the minimum amount of pigment rehas been greatly enhanced in the last 10 years, as the molecuquired for normal optic development. The next 10 years lar pathogenesis of albinism has been better understood. Difshould prove just as exciting as the last. ferent mutations of the tyrosinase gene (TYR) , and their