Study Design and Sample
The Statin Induction and Neuro-Myopathy (SINM) study is a non-interventional, cross-sectional study of neuromuscular side effects in 793 patients treated for hyperlipidemia. Patients were recruited through the Preventive Cardiology Clinic (CT-b, n=214) Hartford Hospital and other affiliated clinics in Hartford, CT (CT-a, N=182), the Cardiovascular Research Institute and a clinic at the San Francisco General Hospital (SF, N=353), and the Lipid Clinic at the Rogosin Institute, Rockefeller University, New York (NY, N=39). Patients provided written informed consent, including permission to use the sample in genomic studies, as approved by the IRBs of all participating institutions.
Definition of Phenotype and Covariates
Patients were assessed for myopathy by a qualified investigator and were classified as suffering myalgia or “muscle pain” or not. A myalgia score of 1 was assigned to patients with definite myalgia when any of the following criteria could be established from the patient medical chart: (1) muscle pain began concurrently with the initiation of statin therapy; (2) muscle pain coincided with an increase in statin dose; (3) muscle pain resolved when the inducing statin was switched to another statin; or (4) muscle pain resolved when statin therapy was discontinued. A myalgia score of 0 was assigned when none of the criteria were met.
For association testing, the dichotomous myalgia score was adjusted for age, gender, heritage, and study site by logistic regression. The probability derived from this regression was then used as a quantitative trait in the association analysis. Heritage was defined as combination of race and ethnicity with Hispanic ethnicity treated as a category in addition to the groups that include European Americans, African American, Asian American, and Native American.
Blood samples for DNA contained either ethylenediamine tetraacetic acid or citrate, and DNA was extracted from leukocytes in 3.5 mL or more of whole blood using a DNA isolation kit (PureGene Gentra®, Qiagen, Valencia, CA). The extracted DNA was genotyped using the Human Hap 1M OmniQuad Genotyping BeadChip of Illumina (San Diego, CA) based on the Infinium Total-Genome Genotyping platform. An iScan scanner was used to read the fluorescence signals from the chip and the raw data processed using the GenomeStudio software. Careful quality control was performed, assuring that all loci were called in at least 99% of individuals. SNPs with allele frequency of less than 3% were excluded. We also determined the genetic gender by the presence or absence of a) heterozygote signals of markers on the X chromosome and b) any signal of markers on the Y chromosome. Comparison with clinically reported gender identified 15 suspect reports, which patients were not considered as part of the overall cohort.
As a further quality control measure, we investigated the genetic population structure using high resolution genome-wide allelic dissimilarity analysis. Allelic dissimilarity was calculated as
between any pair of individuals, involving the genotypes gik for subject i at locus k, for all loci. genotypes gik were 0 for reference homozygotes, 1 for heterozygotes, and 2 for variant homozygotes. Analysis of the resulting distance matrix permitted identification of sample duplications, and unreported family relationships among patients. By comparing the population structure as determined genetically with race and ethnic groups reported clinically, we determined that population structure was adequately accounted for by adjusting the risk factors for reported race and ethnicity. This was confirmed by comparing the score distribution with the null distribution using a q-q plots and genomic inflation factor. The final number of samples used after quality control was 793, the final number of SNPs was 865,483.
The myalgia score was adjusted for covariates as described above, and then analyzed quantitatively using linear regression vs. marker allele count (0, 1, or 2, indicating the number of alternative alleles). The regression p-values were converted to log-scores according to the formula s = - log10 p. Effect sizes were transformed using the logistic function f(z) = 1 / (1 +e-z) to yield probablility of myalgia according to logistic regression. In order to guard against false positive associations caused by non-normal phenotype distribution, small numbered genotype groups and other potential reasons, we also performed a non-parametric permutation analysis, which requires more computation but results in a different set of p-values free of bias caused by divergence from distribution assumptions. The two sets of p-values were compared to identify any statistical anomalies.
For confirmation, multiple SNPs were tested for each candidate locus. Since the candidate genes were derived from biological consideration and did not generally have a genetic marker associated with them, we defined a locus center
as the genomic location in the middle between the first and last gene-associated SNP on the array. Association scores for each SNP within a 400 kb interval around the center were adjusted by dividing the p-value by the number of closer SNPs tested. In addition, the 31 candidates derived from previous studies(6
) were evaluated for statistical significance against a Bonferroni corrected alpha of p < 0.05/31, corresponding to a log-score of 2.8 or greater.