We conducted a multi-ancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry; 58,236 African ancestry; 23,546 Hispanic/Latino; 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (p≤5e-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n=95,768). Meta-analyzing discovery and replication (n=392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our new polygenic risk score reached 16.9% (95% CI=16.1%-17.8%) in European ancestry, 9.5% (95% CI=7.0%-12.2%) in African ancestry, 18.6% (95% CI=15.8%-21.4%) in Hispanic/Latino, and 15.3% (95% CI=12.7%-18.1%) in Asian ancestry, and lower for higher age. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, with potential to personalize prostate cancer screening.

Background:Social barriers to health care, such as food insecurity, financial distress, and housing instability, may impede effective clinical management for individuals with chronic illness. Systematic strategies are needed to more efficiently identify at-risk individuals who may benefit from proactive outreach by health care systems for screening and referral to available social resources.Objective:To create a predictive model to identify a higher likelihood of food insecurity, financial distress, and/or housing instability among adults with multiple chronic medical conditions.Research Design and Subjects:We developed and validated a predictive model in adults with 2 or more chronic conditions who were receiving care within Kaiser Permanente Northern California (KPNC) between January 2017 and February 2020. The model was developed to predict the likelihood of a “yes” response to any of 3 validated self-reported survey questions related to current concerns about food insecurity, financial distress, and/or housing instability. External model validation was conducted in a separate cohort of adult non-Medicaid KPNC members aged 35–85 who completed a survey administered to a random sample of health plan members between April and June 2021 (n = 2820).Measures:We examined the performance of multiple model iterations by comparing areas under the receiver operating characteristic curves (AUCs). We also assessed algorithmic bias related to race/ethnicity and calculated model performance at defined risk thresholds for screening implementation.Results:Patients in the primary modeling cohort (n = 11,999) had a mean age of 53.8 (±19.3) years, 64.7% were women, and 63.9% were of non-White race/ethnicity. The final, simplified model with 30 predictors (including utilization, diagnosis, behavior, insurance, neighborhood, and pharmacy-based variables) had an AUC of 0.68. The model remained robust within different race/ethnic strata.Conclusions:Our results demonstrated that a predictive model developed using information gleaned from the medical record and from public census tract data can be used to identify patients who may benefit from proactive social needs assessment. Depending on the prevalence of social needs in the target population, different risk output thresholds could be set to optimize positive predictive value for successful outreach. This predictive model-based strategy provides a pathway for prioritizing more intensive social risk outreach and screening efforts to the patients who may be in greatest need.

Importance Prior studies suggested that metformin may be associated with reduced dementia incidence, but associations may be confounded by disease severity and prescribing trends. Cessation of metformin therapy in people with diabetes typically occurs due to signs of kidney dysfunction but sometimes is due to less serious adverse effects associated with metformin.Objective To investigate the association of terminating metformin treatment for reasons unrelated to kidney dysfunction with dementia incidence.Design, Setting, and Participants This cohort study was conducted at Kaiser Permanente Northern California, a large integrated health care delivery system, among a cohort of metformin users born prior to 1955 without history of diagnosed kidney disease at metformin initiation. Dementia follow-up began with the implementation of electronic health records in 1996 and continued to 2020. Data were analyzed from November 2021 through September 2023.Exposures A total of 12 220 early terminators, individuals who stopped metformin with normal estimated glomerular filtration rate (eGFR), were compared with routine metformin users, who had not yet terminated metformin treatment or had terminated (with or without restarting) after their first abnormal eGFR measurement. Early terminators were matched with routine users of the same age and gender who had diabetes for the same duration.Main outcomes and measures The outcome of interest was all-cause incident dementia. Follow-up for early terminators and their matched routine users was started at age of termination for the early terminator. Survival models adjusted for sociodemographic characteristics and comorbidities at the time of metformin termination (or matched age). Mediation models with HbA(1c) level and insulin usage 1 and 5 years after termination tested whether changes in blood glucose or insulin usage explained associations between early termination of metformin and dementia incidence.Results The final analytic sample consisted of 12 220 early terminators (5640 women [46.2%]; mean [SD] age at start of first metformin prescription, 59.4 [9.0] years) and 29 126 routine users (13 582 women [46.6%]; mean [SD] age at start of first metformin prescription, 61.1 [8.9] years). Early terminators had 1.21 times the hazard of dementia diagnosis compared with routine users (hazard ratio, 1.21; 95% CI, 1.12 to 1.30). In mediation analysis, contributions to this association by changes in HbA(1c) level or insulin use ranged from no contribution (0.00 years; 95% CI, -0.02 to 0.02 years) for insulin use at 5 years after termination to 0.07 years (95% CI, 0.02 to 0.13 years) for HbA(1c) level at 1 year after termination, suggesting that the association was largely independent of changes in HbA(1c) level and insulin usage.Conclusions and Relevance In this study, terminating metformin treatment was associated with increased dementia incidence. This finding may have important implications for clinical treatment of adults with diabetes and provides additional evidence that metformin is associated with reduced dementia risk.

Supplementary Table S1. Descriptive factors for KP study population, broken down by study. Supplementary Table S2. Genome-wide significant SNPs found in our cohort. Supplementary Table S3. Cis-eQTL expression of rs4646284. Supplementary Table S4. Results at the 105 loci previously found to be associated with prostate cancer. Supplementary Table S5. Risk score of and variance explained by the 105 previously reported hits. Supplementary Figure S1. Manhattan and Q-Q plots of each race/ethnicity and meta-analysis. Supplementary Figure S2. Local plots of novel replicated rs4646284 and suggestive rs2659124. Supplementary Figure S3. Cis-eQTL of SLC22A1 and SLC22A3. Supplementary Figure S4. Comparison of ORs of KP to previous reports by race/ethnicity. Supplementary Figure S5. KP AUC estimates.

BACKGROUND: Unmet social health needs are associated with medication nonadherence. Although pharmacists are well positioned to address medication nonadherence, there is limited experience with screening for and addressing social health needs. OBJECTIVES: To compare the prevalence of social health needs among Medicare patients with higher vs lower social health risk using a predictive model. To also evaluate pre-post changes in medication adherence and health care use following a pharmacist-initiated social health screening. METHODS: A social health screening workflow was implemented into a routine pharmacist adherence program at an integrated health care delivery system. The social health screening was conducted during medication adherence outreach phone calls with Medicare members who were overdue for statin, blood pressure, or diabetes medications. We developed a social health need predictive algorithm to flag higher-risk patients and tested this algorithm against a random subset of lower-risk patients. Screening conversations were guided by a focus group that developed open-ended questions to identify social health needs. Comparisons in social health needs were made between higher- and lower-risk patients. Use and adherence outcomes were compared pre and post for patients who accepted a referral to social health resources and patients who declined a referral. RESULTS: 1,217 patients were contacted and screened for social health needs by pharmacists. Patients flagged by the social risk algorithm were more likely to report social health needs (28.7% vs 12.7% in the unflagged group; P < 0.01). Commonly reported needs included transportation (43%), finances (34%), caregiving (22%), mental health (11%), and food access (10%). 221 patients accepted a referral to a central resource website and call center that connected patients to local services. One year after screening dates, patients who did not accept a referral spent more time in the hospital (mean change +0.7 days, SD = 7.3, P < 0.01), had fewer primary care visits (mean change -0.5 visits, SD = 6.5, P < 0.01), and had a shorter length of membership (mean change -0.4 months, SD = 1.9, P < 0.01). Patients who accepted a referral had increased statin adherence (62.3% adherent pre vs 74.7% post, P = 0.02). CONCLUSIONS: We implemented a workflow for pharmacists to screen for social health needs. The social health need prediction model doubled the identification rate of patients who have needs. Intervening on social health needs during these calls may improve statin adherence and may have no adverse effect on health care utilization or health plan membership. DISCLOSURES: Social health risk predictive model development and validation was funded by the Agency for Healthcare Research and Quality (AHRQ R18HS027343).

Abstract Aims Although highly heritable, the genetic etiology of calcific aortic stenosis (AS) remains incompletely understood. The aim of this study was to discover novel genetic contributors to AS and to integrate functional, expression, and cross-phenotype data to identify mechanisms of AS. Methods and results A genome-wide meta-analysis of 11.6 million variants in 10 cohorts involving 653 867 European ancestry participants (13 765 cases) was performed. Seventeen loci were associated with AS at P ≤ 5 × 10−8, of which 15 replicated in an independent cohort of 90 828 participants (7111 cases), including CELSR2–SORT1, NLRP6, and SMC2. A genetic risk score comprised of the index variants was associated with AS [odds ratio (OR) per standard deviation, 1.31; 95% confidence interval (CI), 1.26–1.35; P = 2.7 × 10−51] and aortic valve calcium (OR per standard deviation, 1.22; 95% CI, 1.08–1.37; P = 1.4 × 10−3), after adjustment for known risk factors. A phenome-wide association study indicated multiple associations with coronary artery disease, apolipoprotein B, and triglycerides. Mendelian randomization supported a causal role for apolipoprotein B-containing lipoprotein particles in AS (OR per g/L of apolipoprotein B, 3.85; 95% CI, 2.90–5.12; P = 2.1 × 10−20) and replicated previous findings of causality for lipoprotein(a) (OR per natural logarithm, 1.20; 95% CI, 1.17–1.23; P = 4.8 × 10−73) and body mass index (OR per kg/m2, 1.07; 95% CI, 1.05–1.9; P = 1.9 × 10−12). Colocalization analyses using the GTEx database identified a role for differential expression of the genes LPA, SORT1, ACTR2, NOTCH4, IL6R, and FADS. Conclusion Dyslipidemia, inflammation, calcification, and adiposity play important roles in the etiology of AS, implicating novel treatments and prevention strategies.

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.

Background: Risk of severe hypoglycemia increases markedly with age in type 2 diabetes (T2D) . For many older patients, discussion of safe de-prescribing strategies is indicated to reduce iatrogenic overtreatment. We examined differences in insulin and sulfonylurea (SU) prescription prevalence among older adults (age ≥ 75 years) by race/ethnicity. Because race/ethnic disparities among Black patients have been attributed to doctor-patient communication barriers, we tested the hypothesis that older Black patients were more likely to be prescribed medicines that can induce severe hypoglycemia. Methods: We studied 18,149 adults (≥75 years) with T2D and a last measured HbA1c ≤ 8.0% between 2019-2021 in Kaiser Permanente Northern California. Electronic health records were used to identify prescription of insulin, SUs, or both. Medication treatment prevalence was stratified by race/ethnicity (Non-Latino White [NLW], Black, Latino, Asian, Other) and compared using chi-square tests. Results: Mean age was 80.5 (±4.8) years; 54% were women; mean HbA1c was 6.9% (±0.7%) , with 42% prescribed insulin, 72% prescribed SUs and 13% prescribed both. Elderly Black and NLW patients had a higher insulin prevalence (both at 45%, p<0.001) , while Asians had the lowest (31%, p=<0.001) . Conversely, Blacks had the lowest SU prevalence (66%, p<0.001) , and Asians had the highest (79%, p<0.001) . A similar pattern was observed in patients with the tightest HbA1c control (< 7.0%; n=8,794) : Black patients had the highest insulin (39%, p<0.001) and lowest SU prevalence (69% p<0.001) , while Asians had the lowest insulin (26%, p<0.001) and highest SU prevalence (81%, p<0.001) . Conclusion We found significant variation in use of high-risk medicines by race/ethnicity. Older Black patients had higher insulin use while older Asian patients had the highest SU use. Efforts to promote safe de-prescribing practices in older adults may need to be tailored to the unique physiologic and cultural needs of different patient groups. Disclosure D.Abdelgadir: None. C.Board: None. D.K.Ranatunga: None. R.W.Grant: None. Funding National Institute on Aging (R01AG068133-S1)

Abstract Few germline genetic variants have been robustly linked with breast cancer outcomes. We conducted trans-ethnic meta genome-wide association study (GWAS) of overall survival (OS) in 3973 breast cancer patients from the Pathways Study, one of the largest prospective breast cancer survivor cohorts. A locus spanning the UACA gene, a key regulator of tumor suppressor Par-4, was associated with OS in patients taking Par-4 dependent chemotherapies, including anthracyclines and anti-HER2 therapy, at a genome-wide significance level ( $$P = 1.27 \times 10^{ - 9}$$ P = 1.27 × 1 0 − 9 ). This association was confirmed in meta-analysis across four independent prospective breast cancer cohorts (combined hazard ratio = 1.84, $$P = 1.28 \times 10^{ - 11}$$ P = 1.28 × 1 0 − 11 ). Transcriptome-wide association study revealed higher UACA gene expression was significantly associated with worse OS ( $$P = 4.68 \times 10^{ - 7}$$ P = 4.68 × 1 0 − 7 ). Our study identified the UACA locus as a genetic predictor of patient outcome following treatment with anthracyclines and/or anti-HER2 therapy, which may have clinical utility in formulating appropriate treatment strategies for breast cancer patients based on their genetic makeup.

Abstract Prior studies suggest a strong genetic influence on breast cancer prognosis. Six genome-wide association studies (GWAS) on breast cancer prognosis have been published to date. However, none of the reported loci was replicated across studies and only two passed genome-wide significance (P < 5 x 10-8). In the Pathways Study, a prospective cohort of breast cancer survivors begun in Kaiser Permanente Northern California (KPNC) in 2006, we carried out a GWAS of overall survival (OS) in 3,973 patients. Trans-ethnic meta-GWAS identified an association with OS of a locus on chromosome 15 that almost reached genome-wide significance (P = 9.42 x 10-8). This locus spanned the UACA gene, a key regulator of tumor suppressor Par-4. We found that receipt of chemotherapy modified the effect of the UACA locus on OS (Pinteraction = 2.4 x 10-4). This observation led us to hypothesize that the UACA locus effect on OS may be specific to Par-4 dependent chemotherapies, which include anti-HER2 therapy and doxorubicin. We stratified patients into two groups, those who received Par-4 dependent chemotherapy agents versus other patients. In separate trans-ethnic meta-GWAS, the UACA locus was significantly associated with OS in patients taking Par-4 dependent chemotherapies (P = 1.27 x 10-9), while no association was observed in the other patients (P = 0.21). To evaluate whether the UACA gene may be responsible for this association, we performed a transcriptome-wide association study (TWAS) of OS in White patients taking Par-4 dependent chemotherapies. Higher UACA gene expression was significantly associated with OS (P = 4.68 x 10-7), the only gene reaching transcriptome-wide significance (P < 4.34 x 10-6). These results suggest that higher UACA expression may inhibit Par-4 induced apoptosis and lead to stronger chemoresistance and worse survival. We attempted to validate our findings in the independent KPNC Genetic Epidemiology Research on Aging (GERA) cohort. The GERA cohort included only 168 White patients with incident breast cancer after DNA collection who received Par-4 dependent chemotherapies. We found a non-significant association (hazard ratio (HR) = 1.46, P = 0.66) consistent with Pathways Study findings. However, the GERA cohort also included 1,983 prevalent breast cancer patients with biospecimen collection after diagnosis. In this group, the risk allele frequency in breast cancer survivors receiving Par-4 dependent chemotherapies was significantly lower than that in the White population (P = 5.50 x 10-3) while the risk allele frequency in the those not receiving these chemotherapies was similar to the population (P = 0.07). This is consistent with Pathways Study observations that the UACA locus risk allele significantly increased risk of mortality in patients taking Par-4 dependent chemotherapies. A higher mortality in breast cancer survivors carrying the risk allele would result in decreased risk allele frequency. We further validated our findings in Shanghai Breast Cancer Survival Study (SBCSS)and Shanghai Breast Cancer Study, which were conducted from 1996 to 2006 in urban Shanghai and recruited 5,575 breast cancer patients. In this independent Asian breast cancer population, the UACA locus was modestly associated with OS in the overall population (HR = 1.18, P = 0.012), and more significantly in 1,289 SBCSS patients who received anthracyclines (HR = 1.66, P = 1.55 x 10-4). This is the first human study suggesting the Par-4 pathway affects breast cancer patient survival with UACA a key modulator of treatment outcomes by anti-Her2 therapy and doxorubicin. Our findings suggest a path toward new predictive pharmacogenetic markers for personalized medicine targeting the Par-4 pathway for breast cancer treatment. Citation Format: Lawrence H Kushi, Qianqian Zhu, Emily Schultz, Jirong Long, Janise M Roh, Emily Valice, Cecile A Laurent, Li Yan, Isaac J Ergas, Warren Davis, Dilrini K Ranatunga, Marilyn L Kwan, Ping-Ping Bao, Wei Zheng, Xiao-Ou Shu, Christine B Ambrosone, Song Yao. Genome-wide association study identifies UACA as a modulator of breast cancer chemoresistance and survival [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr GS2-05.

AbstractTo identify rare variants associated with prostate cancer susceptibility and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we conducted an integrated study of prostate cancer genetic etiology in two cohorts using custom genotyping microarrays, large imputation reference panels, and functional annotation approaches. Specifically, 11,984 men (6,196 prostate cancer cases and 5,788 controls) of European ancestry from Northern California Kaiser Permanente were genotyped and meta-analyzed with 196,269 men of European ancestry (7,917 prostate cancer cases and 188,352 controls) from the UK Biobank. Three novel loci, including two rare variants (European ancestry minor allele frequency < 0.01, at 3p21.31 and 8p12), were significant genome wide in a meta-analysis. Gene-based rare variant tests implicated a known prostate cancer gene (HOXB13), as well as a novel candidate gene (ILDR1), which encodes a receptor highly expressed in prostate tissue and is related to the B7/CD28 family of T-cell immune checkpoint markers. Haplotypic patterns of long-range linkage disequilibrium were observed for rare genetic variants at HOXB13 and other loci, reflecting their evolutionary history. In addition, a polygenic risk score (PRS) of 188 prostate cancer variants was strongly associated with risk (90th vs. 40th–60th percentile OR = 2.62, P = 2.55 × 10−191). Many of the 188 variants exhibited functional signatures of gene expression regulation or transcription factor binding, including a 6-fold difference in log-probability of androgen receptor binding at the variant rs2680708 (17q22). Rare variant and PRS associations, with concomitant functional interpretation of risk mechanisms, can help clarify the full genetic architecture of prostate cancer and other complex traits.Significance:This study maps the biological relationships between diverse risk factors for prostate cancer, integrating different functional datasets to interpret and model genome-wide data from over 200,000 men with and without prostate cancer.See related commentary by Lachance, p. 1637

Background Randomized-controlled trials demonstrate that high coronary heart disease (CHD) polygenic risk score modifies statin CHD relative risk reduction, but it is unknown if the association extends to statin users undergoing routine care. Objectives The primary objective was to determine how statin effectiveness is modified by CHD polygenic risk score in a real-world cohort of primary prevention participants. Methods We determined polygenic risk scores in participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. Cox regression models were used to compare the risk of the cardiovascular outcomes between statin users and matched nonusers. Results The hazard ratio (HR) for statin effectiveness on incident myocardial infarction was similar within 10-year atherosclerotic cardiovascular disease (ASCVD) risk score groups at 0.65 (95% confidence interval [CI] 0.39-1.08; P=0.10), 0.65 (95% CI 0.56-0.77; P=2.1E-7), and 0.67 (95% CI 0.57-0.80; P=4.3E-6) for borderline, intermediate, and high ASCVD groups, respectively. In contrast, statin effectiveness by polygenic risk was largest in the high polygenic risk score group (HR 0.62, 95% CI 0.50-0.77; P=1.4E-5), intermediate in the intermediate polygenic risk score group (HR 0.70, 95% CI 0.61-0.80; P=5.7E-7), and smallest in the low polygenic risk score group (HR 0.86, 95% CI 0.65-1.16; P=0.33). ASCVD risk and statin LDL-C lowering did not differ across polygenic risk score groups. Conclusions In primary prevention patients undergoing routine care, CHD polygenic risk modified statin relative risk reduction of incident myocardial infarction independent of statin LDL-C lowering. Our findings extend prior work by identifying a subset of patients with attenuated clinical benefit from statins.

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.

Background: Left ventricular ejection fraction (EF) is an indicator of cardiac function, usually assessed in individuals with heart failure and other cardiac conditions. Although family studies indicate that EF has an important genetic component with heritability estimates up to 0.61, to date only 6 EF-associated loci have been reported. Methods: Here, we conducted a genome-wide association study (GWAS) of EF in 26 638 adults from the Genetic Epidemiology Research on Adult Health and Aging and the UK Biobank cohorts. Results: A meta-analysis combining results from Genetic Epidemiology Research on Adult Health and Aging and UK Biobank identified a novel locus: TMEM40 on chromosome 3p25 (rs11719526; β=0.47 and P =3.10×10 −8 ) that replicated in Biobank Japan and confirmed recent findings implicating the BAG3 locus on chromosome 10q26 in EF variation, with the strongest association observed for rs17617337 (β=−0.83 and P =8.24×10 −17 ). Although the minor allele frequencies of TMEM40 rs11719526 were generally common (between 0.13 and 0.44) in different ethnic groups, BAG3 rs17617337 was rare (minor allele frequencies<0.05) in Asian and African ancestry populations. These associations were slightly attenuated, after considering antecedent cardiac conditions (ie, heart failure/cardiomyopathy, hypertension, myocardial infarction, atrial fibrillation, valvular disease, and revascularization procedures). This suggests that the effects of the lead variants at TMEM40 or BAG3 on EF are largely independent of these conditions. Conclusions: In this large and multiethnic study, we identified 2 loci, TMEM40 and BAG3 , associated with EF at a genome-wide significance level. Identifying and understanding the genetic determinants of EF is important to better understand the pathophysiology of this strong correlate of cardiac outcomes and to help target the development of future therapies.

Hundreds of loci have been associated with blood pressure 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 (GERA) study participants. In the present study, we subsequently focused on determining putative regulatory regions for these and other tissues of relevance to blood pressure, to both fine-map these loci by pinpointing genes and variants of functional interest within them, and to identify any novel genes. We constructed maps of putative cis-regulatory elements using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Sequence 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. In order to identify genes of interest, we aggregate these variants in these putative cis-regulatory elements within 50Kb of the start or end of genes considered as “expressed” in these tissues or cell types using publicly available gene expression data, and use the deltaSVM scores as weights in the well-known group-wise sequence kernel association test (SKAT). We test for association with both blood pressure traits as well as expression within these tissues or cell types of interest, and identify several genes, including MTHFR , C10orf32 , CSK , NOV , ULK4 , SDCCAG8 , SCAMP5 , RPP25 , HDGFRP3 , VPS37B , and PPCDC . Although our study centers on blood pressure traits, we additionally examined two known genes, SCN5A and NOS1AP involved in the cardiac trait QT interval, in the Atherosclerosis Risk in Communities Study (ARIC), as a positive control, and observed an expected heart-specific effect. Thus, our method may be used to identify variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information. Author Summary Sequence change in genes (“variants”) are linked to the presence and severity of different traits or diseases. However, as genes may be expressed in different tissues and at different times and degrees, using this information is expected to more accurately identify genes of interest. Variants within the genes are essential, but also in the sequences (“regulatory elements”) that control the genes’ expression in different tissues or cell types. In this study, we aim to use this information about expression and variants potentially involved in gene expression regulation to better pinpoint genes and variants in regulatory elements of interest for blood pressure regulation. We do so by taking advantage of such data that are publicly available, and use methods to combine information about variants in aggregate within a gene’s putative regulatory elements in tissues thought to be relevant for blood pressure, and identify several genes, meant to enable experimental follow-up.

The potential association between rare germline genetic variants and prostate cancer (PrCa) susceptibility has been understudied due to challenges with assessing rare variation. Furthermore, although common risk variants for PrCa have shown limited individual effect sizes, their cumulative effect may be of similar magnitude as high penetrance mutations. To identify rare variants associated with PrCa susceptibility, and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we analyzed large population-based cohorts, custom genotyping microarrays, and imputation reference panels in an integrative study of PrCa genetic etiology. In particular, 11,649 men (6,196 PrCa cases, 5,453 controls) of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health, ProHealth Study, and California Men’s Health Study were genotyped and meta-analyzed with 196,269 European-ancestry male subjects (7,917 PrCa cases, 188,352 controls) from the UK Biobank. Six novel loci were genome-wide significant in our meta-analysis, including two rare variants (minor allele frequency < 0.01, at 3p21.31 and 8p12). Gene-based rare variant tests implicated a previously discovered PrCa gene ( HOXB13 ) as well as a novel candidate ( ILDR1 ) highly expressed in prostate tissue. Haplotypic patterns of long-range linkage disequilibrium were observed for rare genetic variants at HOXB13 and other loci, reflecting their evolutionary history. Furthermore, a polygenic risk score (PRS) of 187 known, largely common PrCa variants was strongly associated with risk in non-Hispanic whites (90th vs. 10th decile OR = 7.66, P = 1.80*10-239). Many of the 187 variants exhibited functional signatures of gene expression regulation or transcription factor binding, including a six-fold difference in log-probability of Androgen Receptor binding at the variant rs2680708 (17q22). Our finding of two novel rare variants associated with PrCa should motivate further consideration of the role of low frequency polymorphisms in PrCa, while the considerable effect of PrCa PRS profiles should prompt discussion of their role in clinical practice.

The role of cytochrome P450 (CYP)2C9 and CYP2C19 genetic variation in risk for phenytoin‐induced cutaneous adverse drug events is not well understood independently of the human leukocyte antigen B (HLA‐B)*15:02 risk allele. In the multi‐ethnic resource for Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort, we identified 382 participants who filled a phenytoin prescription between 2005 and 2017. These participants included 21 people (5%) who self‐identified as Asian, 18 (5%) as black, 29 (8%) as white Hispanic, and 308 (81%) as white non‐Hispanic. We identified 264 (69%) CYP2C9*1/*1, 77 (20%) CYP2C9*1/*2, and 29 (8%) CYP2C9*1/*3. We also determined CYP2C19 genotypes, including 112 with the increased activity CYP2C19*17 allele. Using electronic clinical notes, we identified 32 participants (8%) with phenytoin‐induced cutaneous adverse events recorded within 100 days of first phenytoin dispensing. Adjusting for age, sex, daily dose, and race/ethnicity, participants with CYP2C9*1/*3 or CYP2C9*2/*2 genotypes were more likely to develop cutaneous adverse events compared with CYP2C9*1/*1 participants (odds ratio 4.47; 95% confidence interval 1.64–11.69; P < 0.01). Among participants with low‐intermediate and poor CYP2C9 metabolizer genotypes, eight (22%) who also had extensive and rapid CYP2C19 metabolizer genotypes experienced cutaneous adverse events, compared with none of those who also had intermediate CYP2C19 metabolizer genotypes (P = 0.17). Genetic variation reducing CYP2C9 metabolic activity may increase risk for phenytoin‐induced cutaneous adverse events in the absence of the HLA‐B*15:02 risk allele.

Importance Aortic stenosis (AS) has no approved medical treatment. Identifying etiological pathways for AS could identify pharmacological targets. Objective To identify novel genetic loci and pathways associated with AS. Design, Setting, and Participants This genome-wide association study used a case-control design to evaluate 44 703 participants (3469 cases of AS) of self-reported European ancestry from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort (from January 1, 1996, to December 31, 2015). Replication was performed in 7 other cohorts totaling 256 926 participants (5926 cases of AS), with additional analyses performed in 6942 participants from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Follow-up biomarker analyses with aortic valve calcium (AVC) were also performed. Data were analyzed from May 1, 2017, to December 5, 2019. Exposures Genetic variants (615 643 variants) and polyunsaturated fatty acids (omega-6 and omega-3) measured in blood samples. Main Outcomes and Measures Aortic stenosis and aortic valve replacement defined by electronic health records, surgical records, or echocardiography and the presence of AVC measured by computed tomography. Results The mean (SD) age of the 44 703 GERA participants was 69.7 (8.4) years, and 22 019 (49.3%) were men. The rs174547 variant at the FADS1/2 locus was associated with AS (odds ratio [OR] per C allele, 0.88; 95% CI, 0.83-0.93; P = 3.0 x 10(-6)), with genome-wide significance after meta-analysis with 7 replication cohorts totaling 312 118 individuals (9395 cases of AS) (OR, 0.91; 95% CI, 0.88-0.94; P = 2.5 x 10(-8)). A consistent association with AVC was also observed (OR, 0.91; 95% CI, 0.83-0.99; P = .03). A higher ratio of arachidonic acid to linoleic acid was associated with AVC (OR per SD of the natural logarithm, 1.19; 95% CI, 1.09-1.30; P = 6.6 x 10(-5)). In mendelian randomization, increased FADS1 liver expression and arachidonic acid were associated with AS (OR per unit of normalized expression, 1.31 [95% CI, 1.17-1.48; P = 7.4 x 10(-6)]; OR per 5-percentage point increase in arachidonic acid for AVC, 1.23 [95% CI, 1.01-1.49; P = .04]; OR per 5-percentage point increase in arachidonic acid for AS, 1.08 [95% CI, 1.04-1.13; P = 4.1 x 10(-4)]). Conclusions and Relevance Variation at the FADS1/2 locus was associated with AS and AVC. Findings from biomarker measurements and mendelian randomization appear to link omega-6 fatty acid biosynthesis to AS, which may represent a therapeutic target. This genome-wide association study identifies genetic loci and pathways associated with aortic stenosis.

OBJECTIVE:To assess the impact of CYP2C9 variation on phenytoin patient response and clinician prescribing practice where genotype was unknown during treatment.METHODS:A retrospective analysis of Resource on Genetic Epidemiology Research on Adult Health and Aging cohort participants who filled a phenytoin prescription between 1996 and 2017. We used laboratory test results, medication dispensing records, and medical notes to identify associations of CYP2C9 genotype with phenytoin blood concentration, neurologic side effects, and medication dispensing patterns reflecting clinician prescribing practice and patient response.RESULTS:Among 993 participants, we identified 69% extensive, 20% high-intermediate, 10% low-intermediate, and 2% poor metabolizers based on CYP2C9 genotypes. Compared with extensive metabolizer genotype, low-intermediate/poor metabolizer genotype was associated with increased dose-adjusted phenytoin blood concentration [21.3 pg/mL, 95% confidence interval (CI): 13.6-29.0 pg/mL; P < 0.01] and increased risk of neurologic side effects (hazard ratio: 2.40, 95% CI: 1.24-4.64; P < 0.01). Decreased function CYP2C9 genotypes were associated with medication dispensing patterns indicating dose decrease, use of alternative anticonvulsants, and worse adherence, although these associations varied by treatment indication for phenytoin.CONCLUSION:CYP2C9 variation was associated with clinically meaningful differences in clinician prescribing practice and patient response, with potential implications for healthcare utilization and treatment efficacy.