Predicting Self-Reported Social Risk in Medically Complex Adults Using Electronic Health Data.

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.

Telephone-based social health screening by pharmacists in the nonadherent Medicare population.

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).

Metformin Cessation and Dementia Incidence.

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 HbA1c 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 HbA1c 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 HbA1c level at 1 year after termination, suggesting that the association was largely independent of changes in HbA1c 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.

Dyslipidemia, inflammation, calcification, and adiposity in aortic stenosis: a genome-wide study.

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.

Polygenic Risk Score and Statin Relative Risk Reduction for Primary Prevention of Myocardial Infarction in a Real-World Population.

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.

UACA locus is associated with breast cancer chemoresistance and survival.

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 ([Formula: see text]). This association was confirmed in meta-analysis across four independent prospective breast cancer cohorts (combined hazard ratio = 1.84, [Formula: see text]). Transcriptome-wide association study revealed higher UACA gene expression was significantly associated with worse OS ([Formula: see text]). 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.

A Large-Scale Association Study Detects Novel Rare Variants, Risk Genes, Functional Elements, and Polygenic Architecture of Prostate Cancer Susceptibility.

To 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.

Meta-Analysis of 26 638 Individuals Identifies Two Genetic Loci Associated With Left Ventricular Ejection Fraction.

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; ß=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 (ß=-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.

Analysis of putative cis-regulatory elements regulating blood pressure variation.

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.

Associations of CYP2C9 and CYP2C19 Pharmacogenetic Variation with Phenytoin-Induced Cutaneous Adverse Drug Reactions.

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.