Computational pharmacogenotype extraction from clinical next-generation sequencing.

Background: Next-generation sequencing (NGS), including whole genome sequencing (WGS) and whole exome sequencing (WES), is increasingly being used for clinic care. While NGS data have the potential to be repurposed to support clinical pharmacogenomics (PGx), current computational approaches have not been widely validated using clinical data. In this study, we assessed the accuracy of the Aldy computational method to extract PGx genotypes from WGS and WES data for 14 and 13 major pharmacogenes, respectively. Methods: Germline DNA was isolated from whole blood samples collected for 264 patients seen at our institutional molecular solid tumor board. DNA was used for panel-based genotyping within our institutional Clinical Laboratory Improvement Amendments- (CLIA-) certified PGx laboratory. DNA was also sent to other CLIA-certified commercial laboratories for clinical WGS or WES. Aldy v3.3 and v4.4 were used to extract PGx genotypes from these NGS data, and results were compared to the panel-based genotyping reference standard that contained 45 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, TPMT, and VKORC1. Results: Mean WGS read depth was >30x for all variant regions except for G6PD (average read depth was 29 reads), and mean WES read depth was >30x for all variant regions. For 94 patients with WGS, Aldy v3.3 diplotype calls were concordant with those from the genotyping reference standard in 99.5% of cases when excluding diplotypes with additional major star alleles not tested by targeted genotyping, ambiguous phasing, and CYP2D6 hybrid alleles. Aldy v3.3 identified 15 additional clinically actionable star alleles not covered by genotyping within CYP2B6, CYP2C19, DPYD, SLCO1B1, and NUDT15. Within the WGS cohort, Aldy v4.4 diplotype calls were concordant with those from genotyping in 99.7% of cases. When excluding patients with CYP2D6 copy number variation, all Aldy v4.4 diplotype calls except for one CYP3A4 diplotype call were concordant with genotyping for 161 patients in the WES cohort. Conclusion: Aldy v3.3 and v4.4 called diplotypes for major pharmacogenes from clinical WES and WGS data with >99% accuracy. These findings support the use of Aldy to repurpose clinical NGS data to inform clinical PGx.

Retention, Fasting Patterns, and Weight Loss With an Intermittent Fasting App: Large-Scale, 52-Week Observational Study.

BACKGROUND: Intermittent fasting (IF) is an increasingly popular approach to dietary control that focuses on the timing of eating rather than the quantity and content of caloric intake. IF practitioners typically seek to improve their weight and other health factors. Millions of practitioners have turned to purpose-built mobile apps to help them track and adhere to their fasts and monitor changes in their weight and other biometrics. OBJECTIVE: This study aimed to quantify user retention, fasting patterns, and weight loss by users of 2 IF mobile apps. We also sought to describe and model starting BMI, amount of fasting, frequency of weight tracking, and other demographics as correlates of retention and weight change. METHODS: We assembled height, weight, fasting, and demographic data of adult users (ages 18-100 years) of the LIFE Fasting Tracker and LIFE Extend apps from 2018 to 2020. Retention for up to 52 weeks was quantified based on recorded fasts and correlated with user demographics. Users who provided height and at least 2 readings of weight and whose first fast and weight records were contemporaneous were included in the weight loss analysis. Fasting was quantified as extended fasting hours (EFH; hours beyond 12 in a fast) averaged per day (EFH per day). Retention was modeled using a Cox proportional hazards regression. Weight loss was analyzed using linear regression. RESULTS: A total of 792,692 users were followed for retention based on 26 million recorded fasts. Of these, 132,775 (16.7%) users were retained at 13 weeks, 54,881 (6.9%) at 26 weeks, and 16,478 (2.1%) at 52 weeks, allowing 4 consecutive weeks of inactivity. The survival analysis using Cox regression indicated that retention was positively associated with age and exercise and negatively associated with stress and smoking. Weight loss in the qualifying cohort (n=161,346) was strongly correlated with starting BMI and EFH per day, which displayed a positive interaction. Users with a BMI ≥40 kg/m2 lost 13.9% of their starting weight by 52 weeks versus a slight weight gain on average for users with starting BMI <23 kg/m2. EFH per day was an approximately linear predictor of weight loss. By week 26, users lost over 1% of their starting weight per EFH per day on average. The regression analysis using all variables was highly predictive of weight change at 26 weeks (R2=0.334) with starting BMI and EFH per day as the most significant predictors. CONCLUSIONS: IF with LIFE mobile apps appears to be a sustainable approach to weight reduction in the overweight and obese population. Healthy weight and underweight individuals do not lose much weight on average, even with extensive fasting. Users who are obese lose substantial weight over time, with more weight loss in those who fast more.

Analytical Validation of a Computational Method for Pharmacogenetic Genotyping from Clinical Whole Exome Sequencing.

Germline whole exome sequencing from molecular tumor boards has the potential to be repurposed to support clinical pharmacogenomics. However, accurately calling pharmacogenomics-relevant genotypes from exome sequencing data remains challenging. Accordingly, this study assessed the analytical validity of the computational tool, Aldy, in calling pharmacogenomics-relevant genotypes from exome sequencing data for 13 major pharmacogenes. Germline DNA from whole blood was obtained for 164 subjects seen at an institutional molecular solid tumor board. All subjects had whole exome sequencing from Ashion Analytics and panel-based genotyping from an institutional pharmacogenomics laboratory. Aldy version 3.3 was operationalized on the LifeOmic Precision Health Cloud with copy number fixed to two copies per gene. Aldy results were compared with those from genotyping for 56 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, and TPMT. Read depth was >100× for all variants except CYP3A4∗22. For 75 subjects in the validation cohort, all 3393 Aldy variant calls were concordant with genotyping. Aldy calls for 736 diplotypes containing alleles assessed by both platforms were also concordant. Aldy identified additional star alleles not covered by targeted genotyping for 139 diplotypes. Aldy accurately called variants and diplotypes for 13 major pharmacogenes, except for CYP2D6 variants involving copy number variations, thus allowing repurposing of whole exome sequencing to support clinical pharmacogenomics.

The Use of Non-Variant Sites to Improve the Clinical Assessment of Whole-Genome Sequence Data.

Genetic testing, which is now a routine part of clinical practice and disease management protocols, is often based on the assessment of small panels of variants or genes. On the other hand, continuous improvements in the speed and per-base costs of sequencing have now made whole exome sequencing (WES) and whole genome sequencing (WGS) viable strategies for targeted or complete genetic analysis, respectively. Standard WGS/WES data analytical workflows generally rely on calling of sequence variants respect to the reference genome sequence. However, the reference genome sequence contains a large number of sites represented by rare alleles, by known pathogenic alleles and by alleles strongly associated to disease by GWAS. It's thus critical, for clinical applications of WGS and WES, to interpret whether non-variant sites are homozygous for the reference allele or if the corresponding genotype cannot be reliably called. Here we show that an alternative analytical approach based on the analysis of both variant and non-variant sites from WGS data allows to genotype more than 92% of sites corresponding to known SNPs compared to 6% genotyped by standard variant analysis. These include homozygous reference sites of clinical interest, thus leading to a broad and comprehensive characterization of variation necessary to an accurate evaluation of disease risk. Altogether, our findings indicate that characterization of both variant and non-variant clinically informative sites in the genome is necessary to allow an accurate clinical assessment of a personal genome. Finally, we propose a highly efficient extended VCF (eVCF) file format which allows to store genotype calls for sites of clinical interest while remaining compatible with current variant interpretation software.

Enhancing the Predictive Power of Mutations in the C-Terminus of the KCNQ1-Encoded Kv7.1 Voltage-Gated Potassium Channel.

Despite the overrepresentation of Kv7.1 mutations among patients with a robust diagnosis of long QT syndrome (LQTS), a background rate of innocuous Kv7.1 missense variants observed in healthy controls creates ambiguity in the interpretation of LQTS genetic test results. A recent study showed that the probability of pathogenicity for rare missense mutations depends in part on the topological location of the variant in Kv7.1's various structure-function domains. Since the Kv7.1's C-terminus accounts for nearly 50 % of the overall protein and nearly 50 % of the overall background rate of rare variants falls within the C-terminus, further enhancement in mutation calling may provide guidance in distinguishing pathogenic long QT syndrome type 1 (LQT1)-causing mutations from rare non-disease-causing variants in the Kv7.1's C-terminus. Therefore, we have used conservation analysis and a large case-control study to generate topology-based estimative predictive values to aid in interpretation, identifying three regions of high conservation within the Kv7.1's C-terminus which have a high probability of LQT1 pathogenicity.

Distinguishing hypertrophic cardiomyopathy-associated mutations from background genetic noise.

Despite the significant progress that has been made in identifying disease-associated mutations, the utility of the hypertrophic cardiomyopathy (HCM) genetic test is limited by a lack of understanding of the background genetic variation inherent to these sarcomeric genes in seemingly healthy subjects. This study represents the first comprehensive analysis of genetic variation in 427 ostensibly healthy individuals for the HCM genetic test using the "gold standard" Sanger sequencing method validating the background rate identified in the publically available exomes. While mutations are clearly overrepresented in disease, a background rate as high as ∼5 % among healthy individuals prevents diagnostic certainty. To this end, we have identified a number of estimated predictive value-based associations including gene-specific, topology, and conservation methods generating an algorithm aiding in the probabilistic interpretation of an HCM genetic test.

Phylogenetic and physicochemical analyses enhance the classification of rare nonsynonymous single nucleotide variants in type 1 and 2 long-QT syndrome.

BACKGROUND: Hundreds of nonsynonymous single nucleotide variants (nsSNVs) have been identified in the 2 most common long-QT syndrome-susceptibility genes (KCNQ1 and KCNH2). Unfortunately, an ≈3% BACKGROUND: and KCNH2 nsSNVs amongst healthy individuals complicates the ability to distinguish rare pathogenic mutations from similarly rare yet presumably innocuous variants. METHODS AND RESULTS: In this study, 4 tools [(1) conservation across species, (2) Grantham values, (3) sorting intolerant from tolerant, and (4) polymorphism phenotyping] were used to predict pathogenic or benign status for nsSNVs identified across 388 clinically definite long-QT syndrome cases and 1344 ostensibly healthy controls. From these data, estimated predictive values were determined for each tool independently, in concert with previously published protein topology-derived estimated predictive values, and synergistically when ≥3 tools were in agreement. Overall, all 4 tools displayed a statistically significant ability to distinguish between case-derived and control-derived nsSNVs in KCNQ1, whereas each tool, except Grantham values, displayed a similar ability to differentiate KCNH2 nsSNVs. Collectively, when at least 3 of the 4 tools agreed on the pathogenic status of C-terminal nsSNVs located outside the KCNH2/Kv11.1 cyclic nucleotide-binding domain, the topology-specific estimated predictive value improved from 56% to 91%. CONCLUSIONS: Although in silico prediction tools should not be used to predict independently the pathogenicity of a novel, rare nSNV, our results support the potential clinical use of the synergistic utility of these tools to enhance the classification of nsSNVs, particularly for Kv11.1's difficult to interpret C-terminal region.

Distinguishing arrhythmogenic right ventricular cardiomyopathy/dysplasia-associated mutations from background genetic noise.

OBJECTIVES: The aims of this study were to determine the spectrum and prevalence of "background genetic noise" in the arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC) genetic test and to determine genetic associations that can guide the interpretation of a positive test result. BACKGROUND: ARVC is a potentially lethal genetic cardiovascular disorder characterized by myocyte loss and fibrofatty tissue replacement of the right ventricle. Genetic variation among the ARVC susceptibility genes has not been systematically examined, and little is known about the background noise associated with the ARVC genetic test. METHODS: Using direct deoxyribonucleic acid sequencing, the coding exons/splice junctions of PKP2, DSP, DSG2, DSC2, and TMEM43 were genotyped for 93 probands diagnosed with ARVC from the Netherlands and 427 ostensibly healthy controls of various ethnicities. Eighty-two additional ARVC cases were obtained from published reports, and additional mutations were included from the ARVD/C Genetic Variants Database. RESULTS: The overall yield of mutations among ARVC cases was 58% versus 16% in controls. Radical mutations were hosted by 0.5% of control individuals versus 43% of ARVC cases, while 16% of controls hosted missense mutations versus a similar 21% of ARVC cases. Relative to controls, mutations in cases occurred more frequently in non-Caucasians, localized to the N-terminal regions of DSP and DSG2, and localized to highly conserved residues within PKP2 and DSG2. CONCLUSIONS: This study is the first to comprehensively evaluate genetic variation in healthy controls for the ARVC susceptibility genes. Radical mutations are high-probability ARVC-associated mutations, whereas rare missense mutations should be interpreted in the context of race and ethnicity, mutation location, and sequence conservation.

Candidate gene analysis identifies a polymorphism in HLA-DQB1 associated with clozapine-induced agranulocytosis.

OBJECTIVE: Clozapine is considered to be the most efficacious drug to treat schizophrenia, although it is underutilized, partially due to a side effect of agranulocytosis. This analysis of 74 candidate genes was designed to identify an association between sequence variants and clozapine-induced agranulocytosis (CIA). METHOD: Blood and medical history were collected for 33 CIA cases and 54 clozapine-treated controls enrolled between April 2002 and December 2003. Significant markers from 4 genes were then assessed in an independently collected case-control cohort (49 CIA cases, 78 controls). RESULTS: Sequence variants in 5 genes were found to be associated with CIA in the first cohort: HLA-DQB1, HLA-C, DRD1, NTSR1, and CSF2RB. Sequence variants in HLA-DQB1 were also found to be associated with CIA in the second cohort. After refinement analyses of sequence variants in HLA-DQB1, a single SNP (single nucleotide polymorphism), 6672G>C, was found to be associated with risk for CIA; the odds of CIA are 16.9 times greater in patients who carry this marker compared to those who do not. CONCLUSIONS: A sequence variant (6672G>C) in HLA-DQB1 is associated with increased risk for CIA. This marker identifies a subset of patients with an exceptionally high risk of CIA, 1,175% higher than the overall clozapine-treated population under the current blood-monitoring system. Assessing risk for CIA by testing for this and other genetic variants yet to be determined may be clinically useful when deciding whether to begin or continue treatment with clozapine.

Polymorphisms in maternal and fetal genes encoding for proteins involved in extracellular matrix metabolism alter the risk for small-for-gestational-age.

OBJECTIVE: To examine the association between maternal and fetal genetic variants and small-for-gestational-age (SGA). METHODS: A case-control study was conducted in patients with SGA neonates (530 maternal and 436 fetal) and controls (599 maternal and 628 fetal); 190 candidate genes and 775 SNPs were studied. Single-locus, multi-locus and haplotype association analyses were performed on maternal and fetal data with logistic regression, multifactor dimensionality reduction (MDR) analysis, and haplotype-based association with 2 and 3 marker sliding windows, respectively. Ingenuity pathway analysis (IPA) software was used to assess pathways that associate with SGA. RESULTS: The most significant single-locus association in maternal data was with a SNP in tissue inhibitor of metalloproteinase 2 (TIMP2) (rs2277698 OR = 1.71, 95% CI [1.26-2.32], p = 0.0006) while in the fetus it was with a SNP in fibronectin 1 isoform 3 preproprotein (FN1) (rs3796123, OR = 1.46, 95% CI [1.20-1.78], p = 0.0001). Both SNPs were adjusted for potential confounders (maternal body mass index and fetal sex). Haplotype analyses resulted in associations in α 1 type I collagen preproprotein (COL1A1, rs1007086-rs2141279-rs17639446, global p = 0.006) in mothers and FN1 (rs2304573-rs1250204-rs1250215, global p = 0.045) in fetuses. Multi-locus analyses with MDR identified a two SNP model with maternal variants collagen type V α 2 (COL5A2) and plasminogen activator urokinase (PLAU) predicting SGA outcome correctly 59% of the time (p = 0.035). CONCLUSIONS: Genetic variants in extracellular matrix-related genes showed significant single-locus association with SGA. These data are consistent with other studies that have observed elevated circulating fibronectin concentrations in association with increased risk of SGA. The present study supports the hypothesis that DNA variants can partially explain the risk of SGA in a cohort of Hispanic women.

A genetic association study of maternal and fetal candidate genes that predispose to preterm prelabor rupture of membranes (PROM).

OBJECTIVE: We sought to determine whether maternal/fetal single-nucleotide polymorphisms (SNPs) in candidate genes are associated with preterm prelabor rupture of membranes (pPROM). STUDY DESIGN: A case-control study was conducted in patients with pPROM (225 mothers and 155 fetuses) and 599 mothers and 628 fetuses with a normal pregnancy; 190 candidate genes and 775 SNPs were studied. Single locus/haplotype association analyses were performed; false discovery rate was used to correct for multiple testing (q* = 0.15). RESULTS: First, a SNP in tissue inhibitor of metalloproteinase 2 in mothers was significantly associated with pPROM (odds ratio, 2.12; 95% confidence interval, 1.47-3.07; P = .000068), and this association remained significant after correction for multiple comparisons. Second, haplotypes for Alpha 3 type IV collagen isoform precursor in the mother were associated with pPROM (global P = .003). Third, multilocus analysis identified a 3-locus model, which included maternal SNPs in collagen type I alpha 2, defensin alpha 5 gene, and endothelin 1. CONCLUSION: DNA variants in a maternal gene involved in extracellular matrix metabolism doubled the risk of pPROM.

Identification of fetal and maternal single nucleotide polymorphisms in candidate genes that predispose to spontaneous preterm labor with intact membranes.

OBJECTIVE: The purpose of this study was to determine whether maternal/fetal single nucleotide polymorphisms (SNPs) in candidate genes are associated with spontaneous preterm labor/delivery. STUDY DESIGN: A genetic association study was conducted in 223 mothers and 179 fetuses (preterm labor with intact membranes who delivered <37 weeks of gestation [preterm birth (PTB)]), and 599 mothers and 628 fetuses (normal pregnancy); 190 candidate genes and 775 SNPs were studied. Single locus/haplotype association analyses were performed; the false discovery rate was used to correct for multiple testing. RESULTS: The strongest single locus associations with PTB were interleukin-6 receptor 1 (fetus; P=.000148) and tissue inhibitor of metalloproteinase 2 (mother; P=.000197), which remained significant after correction for multiple comparisons. Global haplotype analysis indicated an association between a fetal DNA variant in insulin-like growth factor F2 and maternal alpha 3 type IV collagen isoform 1 (global, P=.004 and .007, respectively). CONCLUSION: An SNP involved in controlling fetal inflammation (interleukin-6 receptor 1) and DNA variants in maternal genes encoding for proteins involved in extracellular matrix metabolism approximately doubled the risk of PTB.

Epidemiologic, molecular, and functional evidence suggest A572D-SCN5A should not be considered an independent LQT3-susceptibility mutation.

BACKGROUND: Considering that approximately 2% of Caucasian controls host rare, nonsynonymous variants in the SCN5A-encoded cardiac sodium channel, caution must be exercised when interpreting SCN5A genetic test results for long QT syndrome (LQTS). OBJECTIVE: The purpose of this study was to determine if A572D-SCN5A is a pathogenic mutation, a possible functional modifier, or background "genetic noise." METHODS: The frequency of A572D was compared between 3,741 LQTS referral cases (mostly Caucasian) and 1,437 Caucasian controls. A572D-SCN5A was engineered into SCN5A using the most commonly spliced transcript (Q1077del, hH1c clone) in the setting of either H558 or R558 for heterologous expression/patch clamp studies in HEK293 cells. RESULTS: A572D-SCN5A was detected in 17 (0.45%) of 3,741 cases compared with 7 (0.49%) of 1,437 controls (P = .82). Among the 17 A572D-positive LQTS referrals, 10 (59%) hosted definite LQTS-causing mutations elsewhere (5 KCNQ1, 3 KCNH2, 2 SCN5A). Functional studies showed no gating kinetic or current density differences compared with wild-type channels in the context of H558 but showed moderate dysfunction when expressed in H558R-SCN5A, with which it is invariably associated. CONCLUSION: There is sufficient evidence to conclude that A572D-SCN5A is not an independent, LQT3-causative mutation. A572D is present in approximately 0.5% of both cases and controls and has a wild-type phenotype when expressed in HEK293 cells. However, in the context of H558R-SCN5A, persistent late sodium current emerges, indicating that A572D/H558R could be a proarrhythmic factor akin to S1103Y. These findings underscore the scrutiny necessary to distinguish truly pathogenic mutations from functional polymorphisms and otherwise innocuous, rare genetic variants in SCN5A. These results also question how much cellular dysfunction for a mutation is required in vitro to support pathogenicity.

An international compendium of mutations in the SCN5A-encoded cardiac sodium channel in patients referred for Brugada syndrome genetic testing.

BACKGROUND: Brugada syndrome (BrS) is a common heritable channelopathy. Mutations in the SCN5A-encoded sodium channel (BrS1) culminate in the most common genotype. OBJECTIVE: This study sought to perform a retrospective analysis of BrS databases from 9 centers that have each genotyped >100 unrelated cases of suspected BrS. METHODS: Mutational analysis of all 27 translated exons in SCN5A was performed. Mutation frequency, type, and localization were compared among cases and 1,300 ostensibly healthy volunteers including 649 white subjects and 651 nonwhite subjects (blacks, Asians, Hispanics, and others) that were genotyped previously. RESULTS: A total of 2,111 unrelated patients (78% male, mean age 39 +/- 15 years) were referred for BrS genetic testing. Rare mutations/variants were more common among BrS cases than control subjects (438/2,111, 21% vs. 11/649, 1.7% white subjects and 31/651, 4.8% nonwhite subjects, respectively, P <10(-53)). The yield of BrS1 genetic testing ranged from 11% to 28% (P = .0017). Overall, 293 distinct mutations were identified in SCN5A: 193 missense, 32 nonsense, 38 frameshift, 21 splice-site, and 9 in-frame deletions/insertions. The 4 most frequent BrS1-associated mutations were E1784K (14x), F861WfsX90 (11x), D356N (8x), and G1408R (7x). Most mutations localized to the transmembrane-spanning regions. CONCLUSION: This international consortium of BrS genetic testing centers has added 200 new BrS1-associated mutations to the public domain. Overall, 21% of BrS probands have mutations in SCN5A compared to the 2% to 5% background rate of rare variants reported in healthy control subjects. Additional studies drawing on the data presented here may help further distinguish pathogenic mutations from similarly rare but otherwise innocuous ones found in cases.

Expression of a common LQT1 mutation in five apparently unrelated families in a regional inherited arrhythmia clinic.

BACKGROUND: The Inherited Arrhythmia Clinic at the University of Western Ontario services a catchment area of 1.5 million people and follows families with inherited arrhythmia syndromes. METHODS: Patients referred for evaluation of long-QT Syndrome (LQTS) are evaluated with resting and standing ECGs, and treadmill exercise testing. Patients with findings consistent with LQTS are offered comprehensive genetic testing with screening of all first-degree relatives of genotype-positive patients. RESULTS: Among 31 probands with disease-causing LQTS mutations, 5 probands from apparently unrelated families of Irish descent were found to have an identical disease causing transmembrane mutation in KCNQ1 (Leu266Pro). Systematic screening of 33 first-degree relatives of genotype-positive individuals detected 15 unaffected and 18 asymptomatic affected family members. Symptoms in 6 patients occurred later in life than reported LQT1 populations (61 +/- 18 years, range 44-89). In this cohort, several family members presented with cardiac arrest during acute myocardial ischemia (n = 2), sudden death, unexplained drowning, and torsade de pointes during exercise testing. There was no identifiable common relative for this cohort after pedigree construction of the previous 4-7 generations. Affected patients had mild QT prolongation at rest with dramatic QT prolongation with exercise. CONCLUSIONS: Genetic testing in this LQTS population suggests a common KCNQ1 Leu266Pro founder effect, with the descendants clustering in our geographical region even though no common relative has been identified. The observations highlight the utility of genotypic and phenotypic correlation and a specialized clinic.

Genetic testing for long-QT syndrome: distinguishing pathogenic mutations from benign variants.

BACKGROUND: Genetic testing for long-QT syndrome (LQTS) has diagnostic, prognostic, and therapeutic implications. Hundreds of causative mutations in 12 known LQTS-susceptibility genes have been identified. Genetic testing that includes the 3 most commonly mutated genes is available clinically. Distinguishing pathogenic mutations from innocuous rare variants is critical to the interpretation of test results. We sought to quantify the value of mutation type and gene/protein region in determining the probability of pathogenicity for mutations. METHODS AND RESULTS: Type, frequency, and location of mutations across KCNQ1 (LQT1), KCNH2 (LQT2), and SCN5A (LQT3) were compared between 388 unrelated "definite" (clinical diagnostic score >or=4 and/or QTc >or=480 ms) cases of LQTS and >1300 healthy controls for each gene. From these data, estimated predictive values (percent of mutations found in definite cases that would cause LQTS) were determined according to mutation type and location. Mutations were 10 times more common in cases than controls (0.58 per case versus 0.06 per control). Missense mutations were the most common, accounting for 78%, 67%, and 89% of mutations in KCNQ1, KCNH2, and SCN5A in cases and >95% in controls. Nonmissense mutations have an estimated predictive value >99% regardless of location. In contrast, location appears to be critical for characterizing missense mutations. Relative frequency of missense mutations between cases and controls ranged from approximately 1:1 in the SCN5A interdomain linker to infinity in the pore, transmembrane, and linker in KCNH2. These correspond to estimated predictive values ranging from 0% in the interdomain linker of SCN5A to 100% in the transmembrane/linker/pore regions of KCNH2. The estimated predictive value is also high in the linker, pore, transmembrane, and C terminus of KCNQ1 and the transmembrane/linker of SCN5A. CONCLUSIONS: Distinguishing pathogenic mutations from rare variants is of critical importance in the interpretation of genetic testing in LQTS. Mutation type, mutation location, and ethnic-specific BACKGROUND: should be viewed as variants of uncertain significance and prompt further investigation to clarify the likelihood of disease causation. However, mutations in regions such as the transmembrane, linker, and pore of KCNQ1 and KCNH2 may be defined confidently as high-probability LQTS-causing mutations. These findings will have implications for other genetic disorders involving mutational analysis.

The SLCO1B1*5 genetic variant is associated with statin-induced side effects.

OBJECTIVES: We sought to identify single nucleotide polymorphisms associated with mild statin-induced side effects. BACKGROUND: Statin-induced side effects can interfere with therapy. Single nucleotide polymorphisms in cytochrome P450 enzymes impair statin metabolism; the reduced function SLCO1B1*5 allele impairs statin clearance and is associated with simvastatin-induced myopathy with creatine kinase (CK) elevation. METHODS: The STRENGTH (Statin Response Examined by Genetic Haplotype Markers) study was a pharmacogenetics study of statin efficacy and safety. Subjects (n = 509) were randomized to atorvastatin 10 mg, simvastatin 20 mg, or pravastatin 10 mg followed by 80 mg, 80 mg, and 40 mg, respectively. We defined a composite adverse event (CAE) as discontinuation for any side effect, myalgia, or CK >3x upper limit of normal during follow-up. We sequenced CYP2D6, CYP2C8, CYP2C9, CYP3A4, and SLCO1B1 and tested 7 reduced function alleles for association with the CAE. RESULTS: The CAE occurred in 99 subjects (54 discontinuations, 49 myalgias, and 9 CK elevations). Sex was associated with CAE (percent female in CAE vs. no CAE groups, 66% vs. 50%, p < 0.01). SLCO1B1*5 was associated with CAE (percent with > or = 1 allele in CAE vs. no CAE groups, 37% vs. 25%, p = 0.03) and those with CAE with no significant CK elevation (p < or = 0.03). Furthermore, there was evidence for a gene-dose effect (percent with CAE in those with 0, 1, or 2 alleles: 19%, 27%, and 50%, trend p = 0.01). Finally, the CAE risk appeared to be greatest in those carriers assigned to simvastatin. CONCLUSIONS: SLCO1B1*5 genotype and female sex were associated mild statin-induced side effects. These findings expand the results of a recent genome-wide association study of statin myopathy with CK >3x normal to milder, statin-induced, muscle side effects.

Spectrum and prevalence of mutations from the first 2,500 consecutive unrelated patients referred for the FAMILION long QT syndrome genetic test.

BACKGROUND: Long QT syndrome (LQTS) is a potentially lethal, highly treatable cardiac channelopathy for which genetic testing has matured from discovery to translation and now clinical implementation. OBJECTIVES: Here we examine the spectrum and prevalence of mutations found in the first 2,500 unrelated cases referred for the FAMILION LQTS clinical genetic test. METHODS: Retrospective analysis of the first 2,500 cases (1,515 female patients, average age at testing 23 +/- 17 years, range 0 to 90 years) scanned for mutations in 5 of the LQTS-susceptibility genes: KCNQ1 (LQT1), KCNH2 (LQT2), SCN5A (LQT3), KCNE1 (LQT5), and KCNE2 (LQT6). RESULTS: Overall, 903 referral cases (36%) hosted a possible LQTS-causing mutation that was absent in >2,600 reference alleles; 821 (91%) of the mutation-positive cases had single genotypes, whereas the remaining 82 patients (9%) had >1 mutation in > or =1 gene, including 52 cases that were compound heterozygous with mutations in >1 gene. Of the 562 distinct mutations, 394 (70%) were missense, 428 (76%) were seen once, and 336 (60%) are novel, including 92 of 199 in KCNQ1, 159 of 226 in KCNH2, and 70 of 110 in SCN5A. CONCLUSION: This cohort increases the publicly available compendium of putative LQTS-associated mutations by >50%, and approximately one-third of the most recently detected mutations continue to be novel. Although control population data suggest that the great majority of these mutations are pathogenic, expert interpretation of genetic test results will remain critical for effective clinical use of LQTS genetic test results.

Prevalence of early-onset atrial fibrillation in congenital long QT syndrome.

BACKGROUND: The prevalence of atrial fibrillation (AF) in the young (age <50 years) is 0.1%, or 1:1,000 persons. Mutations in KCNQ1-, KCNH2-, and KCNA5-encoded potassium channels and SCN5A-encoded sodium channels have been reported in familial AF. A mechanism of atrial torsade has been suggested to occur in patients with congenital long QT syndrome (LQTS). OBJECTIVE: The purpose of this study was to determine the prevalence of AF in patients with congenital LQTS. METHODS: History of documented AF was sought from two independent cohorts. One cohort consisted of 252 consecutive patients (146 females and 106 males, average age at diagnosis 23 +/- 16 years, QTc 465 +/- 51 ms) with genetically proven LQTS seen at Mayo's LQTS Clinic. The second cohort consisted of 205 consecutive patients (133 females and 72 males, average age at testing 23 +/- 16 years, QTc 479 +/- 51 ms) with a positive FAMILION genetic test (PGxHealth) for LQTS. RESULTS: Early-onset AF was documented in 8 (1.7%) of 457 patients, including 6 (2.4%) of 252 patients seen at Mayo and 2 (1%) of 205 patients with a positive FAMILION test. Five (2.4%) of 211 patients with LQT1-susceptibility mutations had documented AF, compared to 0 of 174 patients with LQT2, 1 of 59 patients with LQT3, 1 of 1 patient with Andersen-Tawil syndrome, and 1 of 34 patients with multiple mutations. The average age at diagnosis of AF of the six patients evaluated at Mayo was 24.3 years (range 4-46 years). Early-onset AF (age <50 years) was significantly more common in patients with LQTS compared to population-based prevalence statistics (P <.001, relative risk 17.5). CONCLUSION: Compared to the background prevalence of 0.1%, early-onset AF was observed in almost 2% of patients with genetically proven LQTS and should be viewed as an uncommon but possible LQT-related dysrhythmia. Clinical complaints of palpitations warrant thorough assessment in patients with LQTS.

Pharmacogenetic predictors of statin-mediated low-density lipoprotein cholesterol reduction and dose response.

BACKGROUND: There is interindividual variation in low-density lipoprotein cholesterol (LDLc) lowering by statins and limited study into the genetic associations of the dose dependant LDLc lowering by statins. METHODS AND RESULTS: Five hundred nine patients with hyperlipidemia were randomly assigned atorvastatin 10 mg, simvastatin 20 mg, or pravastatin 10 mg (low-dose phase) followed by 80 mg, 80 mg, and 40 mg (high-dose phase), respectively. Thirty-one genes in statin, cholesterol, and lipoprotein metabolism were sequenced and 489 single nucleotide polymorphisms with minor allele frequencies >2% were tested for associations with percentage LDLc lowering at low doses using multivariable adjusted general linear regression. Significant associations from the analysis at low dose were then repeated at high-dose statins. At low doses, only 1 single nucleotide polymorphism met our experiment-wide significance level, ABCA1 rs12003906. Twenty-six subjects carried the minor allele of rs12003906, which was associated with an attenuated LDLc reduction (LDLc reduction in carriers versus noncarriers -24.1+/-2.6% versus -32.2+/-1.5%; P=0.0001). In addition, we replicated the association with the APOE epsilon3 allele and a reduced LDLc reduction. At high doses, carriers of the minor allele of ABCA1 rs12003906 and the APOE epsilon3 allele improved their LDLc reduction but continued to have a diminished LDLc reduction compared with noncarriers (-30.5+/-4.0% versus -42.0+/-2.4%; P=0.005) and (-38.5+/-1.9% versus -45.3+/-2.8%; P=0.009), respectively. CONCLUSIONS: An intronic single nucleotide polymorphism in ABCA1 and the APOE epsilon3 allele are associated with reduced LDLc lowering by statins and identify individuals who may be resistant to maximal LDLc lowering by statins.