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Statin drugs lower blood cholesterol levels for cardiovascular disease prevention. Women are more likely than men to experience adverse statin effects, particularly new-onset diabetes (NOD) and muscle weakness. Here we find that impaired glucose homeostasis and muscle weakness in statin-treated female mice are associated with reduced levels of the omega-3 fatty acid, docosahexaenoic acid (DHA), impaired redox tone, and reduced mitochondrial respiration. Statin adverse effects are prevented in females by administering fish oil as a source of DHA, by reducing dosage of the X chromosome or the Kdm5c gene, which escapes X chromosome inactivation and is normally expressed at higher levels in females than males. As seen in female mice, we find that women experience more severe reductions than men in DHA levels after statin administration, and that DHA levels are inversely correlated with glucose levels. Furthermore, induced pluripotent stem cells from women who developed NOD exhibit impaired mitochondrial function when treated with statin, whereas cells from men do not. These studies identify X chromosome dosage as a genetic risk factor for statin adverse effects and suggest DHA supplementation as a preventive co-therapy.

OBJECTIVE: Many studies support the notion that polygenic risk scores (PRS) improve risk prediction for coronary heart disease (CHD) beyond conventional risk factors. However, PRS are not yet considered risk-enhancing factor in guidelines. Our objective was to determine the predictive performance of a commercially available PRS (CARDIO inCode-Score®) compared with the Pooled Cohorts Equations (PCE) in a contemporary, multi-ethnic cohort. METHODS: Participants (n = 63,070; 67 % female; 18 % non-European) without prior CHD were followed from 2007 through 12/31/2022. The association between the PRS and incident CHD was assessed using Cox regression adjusting for genetic ancestry and risk factors. Event rates were estimated by categories of PCE and by low/intermediate/high genetic risk within PCE categories; risk discrimination and net reclassification improvement (NRI) were also assessed. RESULTS: There were 3,289 incident CHD events during 14 years of follow-up. Adjusted hazard ratio (aHR) for incident CHD per 1 SD increase in PRS was 1.18 (95 % CI:1.14-1.22), and the aHR for the upper vs lower quintile of the PRS was 1.66 (95 % CI:1.49-1.86). The association was consistent in both sexes, in European participants compared with all minority groups combined and was strongest in the first 5 years of follow-up. The increase in the C-statistic was 0.004 (0.747 vs. 0.751; p < 0.0001); the NRI was 2.4 (0.9-3.8) for the entire cohort and 9.7 (7.5-12.0) for intermediate PCE risk individuals. After incorporating high genetic risk, a further 10 percent of participants at borderline/intermediate PCE risk would be candidates for statin therapy. CONCLUSION: Inclusion of polygenic risk improved identification of primary prevention individuals who may benefit from more intensive risk factor modification.

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

BACKGROUND: Breast cancer survivors are at a higher risk of cardiovascular disease (CVD) morbidity and mortality compared with the general population. The impact of objective social and built neighborhood attributes on CVD risk in a cohort of female breast cancer survivors was examined. METHODS: The 3975 participants came from the Pathways Study, a prospective cohort of women with invasive breast cancer from an integrated health care system in northern California. Women diagnosed with breast cancer from 2006 through 2013 were enrolled on average approximately 2 months after diagnosis. Their baseline addresses were geocoded and appended to neighborhood attributes for racial/ethnic composition, socioeconomic status (SES), population density, urbanization, crime, traffic density, street connectivity, parks, recreational facilities, and retail food environment. Incident CVD events included ischemic heart disease, heart failure, cardiomyopathy, or stroke. Cox proportional hazards models estimated associations of neighborhood attributes with CVD risk, which accounted for clustering by block groups. Fully adjusted models included sociodemographic, clinical, and behavioral factors. RESULTS: During follow-up through December 31, 2018, 340 participants (8.6%) had CVD events. A neighborhood racial/ethnic composition measure, percent of Asian American/Pacific Islander residents (lowest quintile hazard ratio [HR], 1.85; 95% CI, 1.03-3.33), and crime index (highest quartile HR, 1.48; 95% CI, 1.08-2.03) were associated with the risk of CVD events independent of individual SES, hormone receptor status, treatment, cardiometabolic comorbidities, body mass index, and physical activity. CONCLUSIONS: With the application of a socio-ecological framework, how residential environments shape health outcomes in women with breast cancer and affect CVD risk in this growing population can be understood.

AimsThe goal of this study was to examine the association of breast arterial calcification (BAC) presence and quantity with incident atrial fibrillation (AF) in a large cohort of post-menopausal women.Methods and resultsWe conducted a longitudinal cohort study among women free of clinically overt cardiovascular disease and AF at baseline (between October 2012 and February 2015) when they attended mammography screening. Atrial fibrillation incidence was ascertained using diagnostic codes and natural language processing. Among 4908 women, 354 incident cases of AF (7%) were ascertained after a mean (standard deviation) of 7 (2) years of follow-up. In Cox regression adjusting for a propensity score for BAC, BAC presence vs. absence was not significantly associated with AF [hazard ratio (HR) = 1.12; 95% confidence interval (CI), 0.89-1.42; P = 0.34]. However, a significant (a priori hypothesized) age by BAC interaction was found (P = 0.02) such that BAC presence was not associated with incident AF in women aged 60-69 years (HR = 0.83; 95% CI, 0.63-1.15; P = 0.26) but was significantly associated with incident AF in women aged 70-79 years (HR = 1.75; 95% CI, 1.21-2.53; P = 0.003). No evidence of dose-response relationship between BAC gradation and AF was noted in the entire cohort or in age groups separately.ConclusionOur results demonstrate, for the first time, an independent association between BAC and AF in women over age 70 years.

BackgroundEpidemiological studies of interstitial lung disease (ILD) are limited by small numbers and tertiary care bias. Investigators have leveraged the widespread use of electronic health records (EHRs) to overcome these limitations, but struggle to extract patient-level, longitudinal clinical data needed to address many important research questions. We hypothesized that we could automate longitudinal ILD cohort development using the EHR of a large, community-based healthcare system.Study design and methodsWe applied a previously validated algorithm to the EHR of a community-based healthcare system to identify ILD cases between 2012-2020. We then extracted disease-specific characteristics and outcomes using fully automated data-extraction algorithms and natural language processing of selected free-text.ResultsWe identified a community cohort of 5,399 ILD patients (prevalence = 118 per 100,000). Pulmonary function tests (71%) and serologies (54%) were commonly used in the diagnostic evaluation, whereas lung biopsy was rare (5%). IPF was the most common ILD diagnosis (n = 972, 18%). Prednisone was the most commonly prescribed medication (911, 17%). Nintedanib and pirfenidone were rarely prescribed (n = 305, 5%). ILD patients were high-utilizers of inpatient (40%/year hospitalized) and outpatient care (80%/year with pulmonary visit), with sustained utilization throughout the post-diagnosis study period.DiscussionWe demonstrated the feasibility of robustly characterizing a variety of patient-level utilization and health services outcomes in a community-based EHR cohort. This represents a substantial methodological improvement by alleviating traditional constraints on the accuracy and clinical resolution of such ILD cohorts; we believe this approach will make community-based ILD research more efficient, effective, and scalable.

BackgroundPrior studies support the utility of high sensitivity troponin I (hsTnI) for cardiovascular disease (CVD) risk stratification among asymptomatic populations; however, only two prior studies examined women separately. The association between hsTnI and breast arterial calcification is unknown.MethodsCohort study of 2896 women aged 60-79 years recruited after attending mammography screening between 10/2012 and 2/2015. BAC status (presence versus absence) and quantity (calcium mass mg) was determined using digital mammograms. Pre-specified endpoints were incident coronary heart disease (CHD), ischemic stroke, heart failure and its subtypes and all CVD.ResultsAfter 7.4 (SD = 1.7) years of follow-up, 51 CHD, 30 ischemic stroke and 46 heart failure events were ascertained. At a limit of detection of 1.6 ng/L, 98.3 of the cohort had measurable hsTnI concentration. HsTnI in the 4-10 ng/L range were independently associated of CHD (adjusted hazard ratio[aHR] = 2.78; 95% CI, 1.48-5.22; p = 0.002) and all CVD (aHR = 2.06; 95% CI, 1.37-3.09; p = 0.0005) and hsTnI over 10 ng/L was independently associated with CHD (aHR = 4.75; 95% CI, 1.83-12.3; p = 0.001), ischemic stroke (aHR = 3.81; 95% CI, 1.22-11.9; p = 0.02), heart failure (aHR = 3.29; 95% CI, 1.33-8.13; p = 0.01) and all CVD (aHR = 4.78; 95% CI, 2.66-8.59; p

BackgroundPrior studies of the glycemic effect of statins have been inconsistent. Also, most studies have only considered a short duration of statin use; the effect of long-term statin use on fasting glucose (FG) has not been well examined. The aim of this work is to investigate the effect of long-term statin exposure on FG levels.MethodsUsing electronic health record (EHR) data from a large and diverse longitudinal cohort, we defined long-term statin exposure in two ways: the cumulative years of statin use (cumulative supply) and the years' supply-weighted sum of doses (cumulative dose). Simvastatin, lovastatin, atorvastatin and pravastatin were included in the analysis. The relationship between statin exposure and FG was examined using linear regression with mixed effects modeling, comparing statin users before and after initiating statins and statin never-users.ResultsWe examined 593,130 FG measurements from 87,151 individuals over a median follow up of 20 years. Of these, 42,678 were never-users and 44,473 were statin users with a total of 730,031 statin prescriptions. FG was positively associated with cumulative supply of statin but not comulative dose when both measures were in the same model. While statistically significant, the annual increase in FG attributable to statin exposure was modest at only 0.14 mg/dl, with only slight and non-significant differences among statin types.ConclusionsElevation in FG level is associated with statin exposure, but the effect is modest. The results suggest that the risk of a clinically significant increase in FG attributable to long-term statin use is small for most individuals.

Genetic substudies of randomized controlled trials demonstrate that high coronary heart disease (CHD) polygenic risk score modifies statin CHD relative risk reduction; it is unknown if the association extends to statin users undergoing routine care. We sought to determine how statin effectiveness is modified by CHD polygenic risk score in a real-world cohort of participants without previous myocardial infarction. We determined CHD polygenic risk scores in participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. Covariate-adjusted Cox regression models were used to compare the risk of cardiovascular outcomes between statin users and matched nonusers. Statin effectiveness on incident myocardial infarction showed no gradient with increasing 10-year Pooled Cohort Equations atherosclerotic cardiovascular disease (ASCVD) risk across low, borderline, intermediate, and high ASCVD risk score groups. In contrast, statin effectiveness by polygenic risk was largest in the high polygenic risk score group (hazard ratio (HR) 0.41, 95% confidence interval (CI), 0.31-0.53; P = 1.5E-11), intermediate in the intermediate polygenic risk score group (HR 0.56, 95% CI, 0.47-0.66; P = 8.4E-12), and smallest in the low polygenic risk score group (HR 0.67, 95% CI, 0.47-0.97; P = 0.03; P for high vs. low = 0.01). ASCVD risk and statin low-density lipoprotein cholesterol (LDL-C) lowering did not differ across polygenic risk score groups. In patients undergoing routine care, CHD polygenic risk modified statin relative risk reduction of incident myocardial infarction independent of LDL-C lowering. Our findings extend prior work by identifying a subset (i.e., self-identified White individuals with low CHD polygenic risk scores) with attenuated clinical benefit from statins.

BackgroundBreast arterial calcification (BAC), a common incidental finding in mammography, has been shown to be associated with angiographic coronary artery disease and cardiovascular disease (CVD) outcomes. We aimed to (1) examine the association of BAC presence and quantity with hard atherosclerotic CVD (ASCVD) and global CVD; (2) ascertain model calibration, discrimination and reclassification of ASCVD risk; (3) assess the joint effect of BAC presence and 10-year pooled cohorts equations risk on ASCVD.MethodsA cohort study of 5059 women aged 60-79 years recruited after attending mammography screening between October 2012 and February 2015 was conducted in a large health plan in Northern California, United States. BAC status (presence versus absence) and quantity (calcium mass mg) was determined using digital mammograms. Prespecified end points were incident hard ASCVD and a composite of global CVD.ResultsTwenty-six percent of women had BAC >0 mg. After a mean (SD) follow-up of 6.5 (1.6) years, we ascertained 155 (3.0%) ASCVD events and 427 (8.4%) global CVD events. In Cox regression adjusted for traditional CVD risk factors, BAC presence was associated with a 1.51 (95% CI, 1.08-2.11; P=0.02) increased hazard of ASCVD and a 1.23 (95% CI, 1.002-1.52; P=0.04) increased hazard of global CVD. While there was no evidence of dose-response association with ASCVD, a threshold effect was found for global CVD at very high BAC burden (95th percentile when BAC present). BAC status provided additional risk stratification of the pooled cohorts equations risk. We noted improvements in model calibration and reclassification of ASCVD: the overall net reclassification improvement was 0.12 (95% CI, 0.03-0.14; P=0.01) and the bias-corrected clinical-net reclassification improvement was 0.11 (95% CI, 0.01-0.22; P=0.04) after adding BAC status.ConclusionsOur results indicate that BAC has potential utility for primary CVD prevention and, therefore, support the notion that BAC ought to be considered a risk-enhancing factor for ASCVD among postmenopausal women.

The association between the c.521T>C variant allele in SLCO1B1 (reference single nucleotide polymorphism (rs)4149056) and simvastatin-induced myotoxicity was discovered over a decade ago; however, whether this relationship represents a class effect is still not fully known. The aim of this study was to investigate the relationship between rs4149056 genotype and statin-induced myotoxicity in patients taking atorvastatin and lovastatin. Study participants were from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. A total of 233 statin-induced myopathy + rhabdomyolysis cases met the criteria for inclusion and were matched to 2,342 controls. To validate the drug response phenotype, we replicated the previously established association between rs4149056 genotype and simvastatin-induced myotoxicity. In particular, compared with homozygous T allele carriers, there was a significantly increased risk of simvastatin-induced myopathy + rhabdomyolysis in homozygous carriers of the C allele (CC vs. TT, odds ratio [OR] 4.62, 95% confidence interval [CI] 1.58-11.90, P = 0.003). For lovastatin users, homozygous carriers of the C allele were also at increased risk of statin-induced myopathy + rhabdomyolysis (CC vs. TT, OR 4.49, 95% CI 1.68-10.80, P = 0.001). In atorvastatin users, homozygous carriers of the C allele were twice as likely to experience statin-induced myopathy, though this association did not achieve statistical significance (CC vs. TT, OR 2.00, 95% CI 0.44-6.59, P = 0.30). In summary, our findings suggest that the association of rs4149056 with simvastatin-related myotoxicity may also extend to lovastatin. More data is needed to determine the extent of the association in atorvastatin users. Altogether, these data expand the evidence base for informing guidelines of pharmacogenetic-based statin prescribing practices.

Background: Since vascular risk factors are implicated in cognitive decline, and breast arterial calcification (BAC) is related to vascular risk, we postulated that BAC may be associated with cognitive impairment and dementia. Methods: We used a multiethnic cohort of 3,913 asymptomatic women 60-79 years of age recruited after mammography screening at a large health plan in 2012-2015. A BAC mass score (mg) was derived from digital mammograms. Cognitive function was measured at baseline using the Montreal Cognitive Assessment (MoCA) and incident all-cause dementia (n = 49 events; median follow-up = 5.6 years) were ascertained with validated ICD-9 and ICD-10 codes. We used cross-sectional linear regression of MoCA scores on BAC, then multinomial logistic regression predicting mild cognitive impairment not progressing to dementia and incident all-cause dementia and, finally, Cox regression of incident all-cause dementia. Results: No association by linear regression was found between MoCA scores and BAC presence in unadjusted or adjusted analysis. Women with severe (upper tertile) BAC had a MoCA score lower by 0.58 points (standard error [SE] = 0.18) relative to women with no BAC. However, this difference disappeared after multivariate adjustment. No significant associations were found in multinomial logistic regression for either BAC presence or gradation in unadjusted or adjusted analysis. No significant associations were found between BAC presence with incident all-cause dementia (fully adjusted hazard ratio = 0.74; 95% confidence interval: 0.39-1.39). Likewise, no significant association with incident all-cause dementia was noted for BAC gradation. Conclusions: Our results do not support the hypothesis that BAC presence or gradation may contribute to cognitive impairment or development of all-cause dementia.

BackgroundIdiopathic pulmonary fibrosis (IPF) is a rare, chronic lung disease associated with substantial symptom burden, morbidity, and cost. Delivery of high-quality effective care in IPF requires understanding health-care resource utilization (HRU) patterns; however, longitudinal data from real-world populations are limited.Research questionThis study aimed to define HRU attributable to IPF by evaluating a longitudinal cohort of community patients with IPF compared with matched control subjects.Study design and methodsIncident IPF cases were identified in the Kaiser Permanente Northern California electronic health records (2000-2015) using case-validated code-based algorithms. IPF cases were compared with matched control subjects by age, sex, and length of enrollment. Annual rates of HRU measures were assessed during the 5 years pre- and postdiagnosis. Poisson generalized estimating equations were used to estimate adjusted case-control differences in HRU. IPF treatment trends were assessed before and after the availability of IPF-specific medications.ResultsA total of 691 IPF cases were identified and matched with 3,452 control subjects. Adjusted rates of all diagnostic procedures were significantly increased (P < .001) for IPF cases compared with control subjects in both the pre- and postindex periods, including chest CT scans (pre-relative risk [RR], 80.35; post-RR, 32.79), 6-min walk tests (pre-RR, 20.81; post-RR, 34.49), and pulmonary function tests (pre-RR, 9.50; post-RR, 13.24). All-cause hospitalizations (pre-RR, 1.42; post-RR, 2.33) and outpatient visits (pre-RR, 1.22; post-RR, 1.80) were significantly higher among cases compared with control subjects during both the preindex (P < .05) and postindex (P < .001) periods. We observed use of immunosuppressive and IPF-specific therapies prior to diagnosis, and high rates of corticosteroid use before and after diagnosis.InterpretationThis study defines a marked increase in HRU in patients with IPF compared with control subjects, with accelerated use beginning at least 1 year prediagnosis and elevated use sustained over the following 5 years. To our knowledge, this is the first study to evaluate longitudinal medication trends in IPF. Collectively, this information is foundational to advancing IPF care delivery models and supporting clinical decision-making.

Hundreds of loci have been associated with blood pressure (BP) traits from many genome-wide association studies. We identified an enrichment of these loci in aorta and tibial artery expression quantitative trait loci in our previous work in ~100 000 Genetic Epidemiology Research on Aging study participants. In the present study, we sought to fine-map known loci and identify novel genes by determining putative regulatory regions for these and other tissues relevant to BP. We constructed maps of putative cis-regulatory elements (CREs) using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Variants within these regions may be evaluated quantitatively for their tissue- or cell-type-specific regulatory impact using deltaSVM functional scores, as described in our previous work. We aggregate variants within these putative CREs within 50 Kb of the start or end of 'expressed' genes in these tissues or cell types using public expression data and use deltaSVM scores as weights in the group-wise sequence kernel association test to identify candidates. We test for association with both BP traits and expression within these tissues or cell types of interest and identify the candidates MTHFR, C10orf32, CSK, NOV, ULK4, SDCCAG8, SCAMP5, RPP25, HDGFRP3, VPS37B and PPCDC. Additionally, we examined two known QT interval genes, SCN5A and NOS1AP, in the Atherosclerosis Risk in Communities Study, as a positive control, and observed the expected heart-specific effect. Thus, our method identifies variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information.

Context:The association between bone mineral density (BMD) and breast arterial calcification (BAC) remains poorly understood and controversial. Objective:The objective of this article is to examine the association between BMD and BAC in a large cohort of postmenopausal women undergoing routine mammography. Design:A cross-sectional analysis of baseline data from a multiethnic cohort was performed. Setting:The setting for this analysis is an integrated health care delivery system in Northern California in the United States. Patients:A total of 1273 women age 60 to 79 years (mean age, 67 years) were recruited within 12 months of screening mammography. Main outcome measure:A BAC score (mg) was obtained from digital mammograms using a novel densitometry method. BAC presence was defined as a BAC score greater than 0 mg, and severe BAC as a BAC score greater than 20 mg. Results:Overall, 53% of women had osteopenia and 21% had osteoporosis. The prevalence of BAC greater than 0 mg was 29%, 30%, and 29% among women with normal BMD, osteopenia, and osteoporosis, respectively (P = 0.98). The prevalence of BAC greater than 20 mg was 5%, 3%, and 5% among women with normal BMD, osteopenia and osteoporosis, respectively (P = .65). The odds ratios (ORs) of BAC greater than 0 mg vs BAC = 0 mg after multivariable adjustment were 1.09 (95% CI, 0.81-1.48; P = .54) for osteopenia and 0.99 (95% CI, 0.69-1.48; P = .98) for osteoporosis. The adjusted ORs for BAC greater than 20 mg vs BAC 20 mg or less were 1.03 (95% CI, 0.52-2.01; P = .93) for osteopenia and 1.89 (95 CI, 0.81-4.47; P = .14) for osteoporosis. Conclusion:Our findings do not support an association of either osteopenia or osteoporosis with BAC presence or severity among postmenopausal women.

In pharmacogenomic studies of quantitative change, any association between genetic variants and the pretreatment (baseline) measurement can bias the estimate of effect between those variants and drug response. A putative solution is to adjust for baseline. We conducted a series of genome-wide association studies (GWASs) for low-density lipoprotein cholesterol (LDL-C) response to statin therapy in 34,874 participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort as a case study to investigate the impact of baseline adjustment on results generated from pharmacogenomic studies of quantitative change. Across phenotypes of statin-induced LDL-C change, baseline adjustment identified variants from six loci meeting genome-wide significance (SORT/CELSR2/PSRC1, LPA, SLCO1B1, APOE, APOB, and SMARCA4/LDLR). In contrast, baseline-unadjusted analyses yielded variants from three loci meeting the criteria for genome-wide significance (LPA, APOE, and SLCO1B1). A genome-wide heterogeneity test of baseline versus statin on-treatment LDL-C levels was performed as the definitive test for the true effect of genetic variants on statin-induced LDL-C change. These findings were generally consistent with the models not adjusting for baseline signifying that genome-wide significant hits generated only from baseline-adjusted analyses (SORT/CELSR2/PSRC1, APOB, SMARCA4/LDLR) were likely biased. We then comprehensively reviewed published GWASs of drug-induced quantitative change and discovered that more than half (59%) inappropriately adjusted for baseline. Altogether, we demonstrate that (1) baseline adjustment introduces bias in pharmacogenomic studies of quantitative change and (2) this erroneous methodology is highly prevalent. We conclude that it is critical to avoid this common statistical approach in future pharmacogenomic studies of quantitative change.

In pharmacogenomic studies of quantitative change, any association between genetic variants and the pretreatment (baseline) measurement can bias the estimate of effect between those variants and drug response. A putative solution is to adjust for baseline. We conducted a series of genome-wide association studies (GWASs) for low-density lipoprotein cholesterol (LDL-C) response to statin therapy in 34,874 participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort as a case study to investigate the impact of baseline adjustment on results generated from pharmacogenomic studies of quantitative change. Across phenotypes of statin-induced LDL-C change, baseline adjustment identified variants from six loci meeting genome-wide significance (SORT/CELSR2/PSRC1, LPA, SLCO1B1, APOE, APOB, and SMARCA4/LDLR). In contrast, baseline-unadjusted analyses yielded variants from three loci meeting the criteria for genome-wide significance (LPA, APOE, and SLCO1B1). A genome-wide heterogeneity test of baseline versus statin on-treatment LDL-C levels was performed as the definitive test for the true effect of genetic variants on statin-induced LDL-C change. These findings were generally consistent with the models not adjusting for baseline signifying that genome-wide significant hits generated only from baseline-adjusted analyses (SORT/CELSR2/PSRC1, APOB, SMARCA4/LDLR) were likely biased. We then comprehensively reviewed published GWASs of drug-induced quantitative change and discovered that more than half (59%) inappropriately adjusted for baseline. Altogether, we demonstrate that (1) baseline adjustment introduces bias in pharmacogenomic studies of quantitative change and (2) this erroneous methodology is highly prevalent. We conclude that it is critical to avoid this common statistical approach in future pharmacogenomic studies of quantitative change.

Patient-derived induced pluripotent stem cells (iPSCs) have become a promising resource for exploring genetics of complex diseases, discovering new drugs, and advancing regenerative medicine. Increasingly, laboratories are creating their own banks of iPSCs derived from diverse donors. However, there are not yet standardized guidelines for qualifying these cell lines, i.e., distinguishing between bona fide human iPSCs, somatic cells, and imperfectly reprogrammed cells. Here, we report the establishment of a panel of 30 iPSCs from CD34+ peripheral blood mononuclear cells, of which 10 were further differentiated in vitro into all three germ layers. We characterized these different cell types with commonly used pluripotent and lineage specific markers, and showed that NES, TUBB3, and OTX2 cannot be reliably used as ectoderm differentiation markers. Our work highlights the importance of marker selection in iPSC authentication, and the need for the field to establish definitive standard assays.

BackgroundBreast arterial calcification (BAC) may be a predictor of cardiovascular events and is highly prevalent in persons with end-stage kidney disease. However, few studies to date have examined the association between mild-to-moderate kidney function and proteinuria with BAC.MethodsWe prospectively enrolled women with no prior cardiovascular disease aged 60 to 79 years undergoing mammography screening at Kaiser Permanente Northern California between 10/24/2012 and 2/13/2015. Urine albumin-to-creatinine ratio (uACR), along with specific laboratory, demographic, and medical data, were measured at the baseline visit. Baseline estimated glomerular filtration rate (eGFR), medication history, and other comorbidities were identified from self-report and/or electronic medical records. BAC presence and gradation (mass) was measured by digital quantification of full-field mammograms.ResultsAmong 3,507 participants, 24.5% were aged ≥70 years, 63.5% were white, 7.5% had eGFR 0 mg) was 27.9%. Neither uACR ≥30 mg/g nor uACR ≥300 were significantly associated with BAC in crude or multivariable analyses. Reduced eGFR was associated with BAC in univariate analyses (odds ratio 1.53, 95% CI: 1.18-2.00), but the association was no longer significant after adjustment for potential confounders. Results were similar in various sensitivity analyses that used different BAC thresholds or analytic approaches.ConclusionsAmong women without cardiovascular disease undergoing mammography screening, reduced eGFR and albuminuria were not significantly associated with BAC.

Purpose: Women with breast cancer (BC) are at high risk of developing cardiovascular disease (CVD). We examined adherence to CVD medications and their association with major CVD events over 14 years of follow-up in the Pathways Heart Study, a prospective study of 4,776 stage I-III BC patients diagnosed from 2005–2013. Methods: Eligibility included being alive 6 months post-BC diagnosis, with dyslipidemia, hypertension, or diabetes at diagnosis along with ≥1 prior outpatient order or dispensing for a statin, anti-hypertensive, or diabetes medication, respectively, in the 30 months prior. Medication adherence was measured from pharmacy data to calculate cumulative average adherence (CAA). Incident heart failure (HF), ischemic heart disease (IHD), and stroke were determined via validated diagnosis and procedure codes. Working marginal structural models (MSM) fitted with inverse probability weighting evaluated the effect of adherence regimens on the hazards for each CVD event, while controlling for baseline and time-varying confounders. MSM parameterizations included: 1) CAA<100% versus CAA = 100% (ref), 2) CAA<80% versus CAA≥80% (ref) and 3) CAA<80% versus 80%≤CAA<100% versus CAA = 100%. Results: Poor statin adherence (CAA<80%) was associated with higher risk of composite CVD (HR = 2.54; 95% CI: 1.09, 5.94) versus CAA≥80%. Poor statin adherence was also associated with a higher risk of stroke (HR = 8.13; 95% CI: 2.03, 32.51) but not risk of IHD and HF. Further, compared with perfect adherence (CAA = 100%), good adherence (80%≤CAA<100%) was associated with lower risk (HR = 0.35; 95% CI: 0.13, 0.92) while poor adherence (CAA<80%) was associated with higher risk of composite CVD (HR = 2.45; 95% CI: 1.05, 5.70). Levels of adherence to anti-hypertensives and diabetes medications had mixed or null associations with risk of CVD. Conclusions: Maintaining good adherence (≥80%) to statins after BC treatment is beneficial for cardiovascular health in patients with dyslipidemia. Future studies should determine factors associated with lower adherence to statins and ways to improve adherence. [ABSTRACT FROM AUTHOR]

BackgroundLow-density lipoprotein cholesterol (LDL-C) response to statin therapy has not been fully elucidated in real-world populations. The primary objective of this study was to characterize statin LDL-C dose-response and its heritability in a large, multiethnic population of statin users.MethodsWe determined the effect of statin dosing on lipid measures utilizing electronic health records in 33 139 statin users from the Kaiser Permanente GERA cohort (Genetic Epidemiology Research on Adult Health and Aging). The relationship between statin defined daily dose and lipid parameter response (percent change) was determined.ResultsDefined daily dose and LDL-C response was associated in a log-linear relationship (β, -6.17; SE, 0.09; P

A genome-wide association study (GWAS) of 94,674 ancestrally diverse Kaiser Permanente members using 478,866 longitudinal electronic health record (EHR)-derived measurements for untreated serum lipid levels empowered multiple new findings: 121 new SNP associations (46 primary, 15 conditional, and 60 in meta-analysis with Global Lipids Genetic Consortium data); an increase of 33-42% in variance explained with multiple measurements; sex differences in genetic impact (greater impact in females for LDL, HDL, and total cholesterol and the opposite for triglycerides); differences in variance explained among non-Hispanic whites, Latinos, African Americans, and East Asians; genetic dominance and epistatic interaction, with strong evidence for both at the ABO and FUT2 genes for LDL; and tissue-specific enrichment of GWAS-associated SNPs among liver, adipose, and pancreas eQTLs. Using EHR pharmacy data, both LDL and triglyceride genetic risk scores (477 SNPs) were strongly predictive of age at initiation of lipid-lowering treatment. These findings highlight the value of longitudinal EHRs for identifying new genetic features of cholesterol and lipoprotein metabolism with implications for lipid treatment and risk of coronary heart disease.

RationalePopulation-based studies of idiopathic pulmonary fibrosis (IPF) in the United States have been limited by reliance on diagnostic code-based algorithms that lack clinical validation.ObjectivesTo validate a well-accepted International Classification of Diseases, Ninth Revision, code-based algorithm for IPF using patient-level information and to develop a modified algorithm for IPF with enhanced predictive value.MethodsThe traditional IPF algorithm was used to identify potential cases of IPF in the Kaiser Permanente Northern California adult population from 2000 to 2014. Incidence and prevalence were determined overall and by age, sex, and race/ethnicity. A validation subset of cases (n = 150) underwent expert medical record and chest computed tomography review. A modified IPF algorithm was then derived and validated to optimize positive predictive value.ResultsFrom 2000 to 2014, the traditional IPF algorithm identified 2,608 cases among 5,389,627 at-risk adults in the Kaiser Permanente Northern California population. Annual incidence was 6.8/100,000 person-years (95% confidence interval [CI], 6.1-7.7) and was higher in patients with older age, male sex, and white race. The positive predictive value of the IPF algorithm was only 42.2% (95% CI, 30.6 to 54.6%); sensitivity was 55.6% (95% CI, 21.2 to 86.3%). The corrected incidence was estimated at 5.6/100,000 person-years (95% CI, 2.6-10.3). A modified IPF algorithm had improved positive predictive value but reduced sensitivity compared with the traditional algorithm.ConclusionsA well-accepted International Classification of Diseases, Ninth Revision, code-based IPF algorithm performs poorly, falsely classifying many non-IPF cases as IPF and missing a substantial proportion of IPF cases. A modification of the IPF algorithm may be useful for future population-based studies of IPF.

Coronary artery disease is a major cause of death in women. Breast arterial calcifications (BACs), detected inmammograms, can be useful riskmarkers associated with the disease. We investigate the feasibility of automated and accurate detection ofBACsinmammograms for risk assessment of coronary artery disease. We develop a 12-layer convolutional neural network to discriminate BAC from non-BAC and apply a pixelwise, patch-based procedure for BAC detection. To assess the performance of the system, we conduct a reader study to provide ground-truth information using the consensus of human expert radiologists. We evaluate the performance using a set of 840 full-field digital mammograms from 210 cases, using both free-responsereceiveroperatingcharacteristic (FROC) analysis and calcium mass quantification analysis. The FROC analysis shows that the deep learning approach achieves a level of detection similar to the human experts. The calcium mass quantification analysis shows that the inferred calcium mass is close to the ground truth, with a linear regression between them yielding a coefficient of determination of 96.24%. Taken together, these results suggest that deep learning can be used effectively to develop an automated system for BAC detection inmammograms to help identify and assess patients with cardiovascular risks.

Longitudinal electronic health records on 99,785 Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort individuals provided 1,342,814 systolic and diastolic blood pressure measurements for a genome-wide association study on long-term average systolic, diastolic, and pulse pressure. We identified 39 new loci among 75 genome-wide significant loci (P ≤ 5 × 10-8), with most replicating in the combined International Consortium for Blood Pressure (ICBP; n = 69,396) and UK Biobank (UKB; n = 152,081) studies. Combining GERA with ICBP yielded 36 additional new loci, with most replicating in UKB. Combining all three studies (n = 321,262) yielded 241 additional genome-wide significant loci, although no replication sample was available for these. All associated loci explained 2.9%, 2.5%, and 3.1% of variation in systolic, diastolic, and pulse pressure, respectively, in GERA non-Hispanic whites. Using multiple blood pressure measurements in GERA doubled the variance explained. A normalized risk score was associated with time to onset of hypertension (hazards ratio = 1.18, P = 8.2 × 10-45). Expression quantitative trait locus analysis of blood pressure loci showed enrichment in aorta and tibial artery.

In COPD, body composition studies have focused primarily on low BMI. We examined obesity (BMI ≥ 30 kg/m(2)) as a risk factor for poor function and longitudinal functional decline. Data from a longitudinal cohort of adults with COPD (n = 1096) and an age- and sex-matched comparison group collected in two in-person visits ∼49 months apart were analyzed. Two measures of functioning were examined: six-minute walk distance (6MWD) and Short Physical Performance Battery (SPPB). Multivariate regression analyses examined relationships of obesity with functioning. Secondary analyses stratified by GOLD classification (GOLD-0/1, GOLD-2, GOLD-3/4). Obesity (53% of COPD cohort) was associated cross-sectionally with 6MWD and SPPB in COPD, and only with 6MWD in the comparison group. Obesity predicted significant functional decline in 6MWD for individuals with COPD (odds ratio (OR) for decline [95% CI] 1.8 [1.1, 2.9]), but not the comparison group. Secondary analyses revealed that the risk of decline was significant only in those with more severe COPD (GOLD 3/4, OR = 2.3 [1.0, 5.4]). Obesity was highly prevalent and was associated with poor function concurrently and with subsequent decline in 6MWD in COPD. Obesity in COPD should be considered a risk not only for more co-morbidities and greater health care use, but also for functional decline.

The Kaiser Permanente (KP) Research Program on Genes, Environment and Health (RPGEH), in collaboration with the University of California-San Francisco, undertook genome-wide genotyping of >100,000 subjects that constitute the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The project, which generated >70 billion genotypes, represents the first large-scale use of the Affymetrix Axiom Genotyping Solution. Because genotyping took place over a short 14-month period, creating a near-real-time analysis pipeline for experimental assay quality control and final optimized analyses was critical. Because of the multi-ethnic nature of the cohort, four different ethnic-specific arrays were employed to enhance genome-wide coverage. All assays were performed on DNA extracted from saliva samples. To improve sample call rates and significantly increase genotype concordance, we partitioned the cohort into disjoint packages of plates with similar assay contexts. Using strict QC criteria, the overall genotyping success rate was 103,067 of 109,837 samples assayed (93.8%), with a range of 92.1-95.4% for the four different arrays. Similarly, the SNP genotyping success rate ranged from 98.1 to 99.4% across the four arrays, the variation depending mostly on how many SNPs were included as single copy vs. double copy on a particular array. The high quality and large scale of genotype data created on this cohort, in conjunction with comprehensive longitudinal data from the KP electronic health records of participants, will enable a broad range of highly powered genome-wide association studies on a diversity of traits and conditions.

Using genome-wide genotypes, we characterized the genetic structure of 103,006 participants in the Kaiser Permanente Northern California multi-ethnic Genetic Epidemiology Research on Adult Health and Aging Cohort and analyzed the relationship to self-reported race/ethnicity. Participants endorsed any of 23 race/ethnicity/nationality categories, which were collapsed into seven major race/ethnicity groups. By self-report the cohort is 80.8% white and 19.2% minority; 93.8% endorsed a single race/ethnicity group, while 6.2% endorsed two or more. Principal component (PC) and admixture analyses were generally consistent with prior studies. Approximately 17% of subjects had genetic ancestry from more than one continent, and 12% were genetically admixed, considering only nonadjacent geographical origins. Self-reported whites were spread on a continuum along the first two PCs, indicating extensive mixing among European nationalities. Self-identified East Asian nationalities correlated with genetic clustering, consistent with extensive endogamy. Individuals of mixed East Asian-European genetic ancestry were easily identified; we also observed a modest amount of European genetic ancestry in individuals self-identified as Filipinos. Self-reported African Americans and Latinos showed extensive European and African genetic ancestry, and Native American genetic ancestry for the latter. Among 3741 genetically identified parent-child pairs, 93% were concordant for self-reported race/ethnicity; among 2018 genetically identified full-sib pairs, 96% were concordant; the lower rate for parent-child pairs was largely due to intermarriage. The parent-child pairs revealed a trend toward increasing exogamy over time; the presence in the cohort of individuals endorsing multiple race/ethnicity categories creates interesting challenges and future opportunities for genetic epidemiologic studies.

The Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort includes DNA specimens extracted from saliva samples of 110,266 individuals. Because of its relationship to aging, telomere length measurement was considered an important biomarker to develop on these subjects. To assay relative telomere length (TL) on this large cohort over a short time period, we created a novel high throughput robotic system for TL analysis and informatics. Samples were run in triplicate, along with control samples, in a randomized design. As part of quality control, we determined the within-sample variability and employed thresholds for the elimination of outlying measurements. Of 106,902 samples assayed, 105,539 (98.7%) passed all quality control (QC) measures. As expected, TL in general showed a decline with age and a sex difference. While telomeres showed a negative correlation with age up to 75 years, in those older than 75 years, age positively correlated with longer telomeres, indicative of an association of longer telomeres with more years of survival in those older than 75. Furthermore, while females in general had longer telomeres than males, this difference was significant only for those older than age 50. An additional novel finding was that the variance of TL between individuals increased with age. This study establishes reliable assay and analysis methodologies for measurement of TL in large, population-based human studies. The GERA cohort represents the largest currently available such resource, linked to comprehensive electronic health and genotype data for analysis.

BACKGROUND: Adjustment for differing risks among patients is usually incorporated into newer payment approaches, and current risk models rely on age, sex, and diagnosis codes. It is unknown the extent to which controlling additionally for disease severity improves cost prediction. Failure to adjust for within-disease variation may create incentives to avoid sicker patients. We address this issue among patients with chronic obstructive pulmonary disease (COPD). METHODS: Cost and clinical data were collected prospectively from 1202 COPD patients at Kaiser Permanente. Baseline analysis included age, sex, and diagnosis codes (using the Diagnostic Cost Group Relative Risk Score) in a general linear model predicting total medical costs in the following year. We determined whether adding COPD severity measures-forced expiratory volume in 1 second, 6-Minute Walk Test, dyspnea score, body mass index, and BODE Index (composite of the other 4 measures)-improved predictions. Separately, we examined household income as a cost predictor. RESULTS: Mean costs were $12,334/y. Controlling for Relative Risk Score, each ½ SD worsening in COPD severity factor was associated with $629 to $1135 in increased annual costs (all P

BackgroundAdjustment for differing risks among patients is usually incorporated into newer payment approaches, and current risk models rely on age, sex, and diagnosis codes. It is unknown the extent to which controlling additionally for disease severity improves cost prediction. Failure to adjust for within-disease variation may create incentives to avoid sicker patients. We address this issue among patients with chronic obstructive pulmonary disease (COPD).MethodsCost and clinical data were collected prospectively from 1202 COPD patients at Kaiser Permanente. Baseline analysis included age, sex, and diagnosis codes (using the Diagnostic Cost Group Relative Risk Score) in a general linear model predicting total medical costs in the following year. We determined whether adding COPD severity measures-forced expiratory volume in 1 second, 6-Minute Walk Test, dyspnea score, body mass index, and BODE Index (composite of the other 4 measures)-improved predictions. Separately, we examined household income as a cost predictor.ResultsMean costs were $12,334/y. Controlling for Relative Risk Score, each ½ SD worsening in COPD severity factor was associated with $629 to $1135 in increased annual costs (all P