Development and Validation of a Diabetic Retinopathy Risk Stratification Algorithm.

OBJECTIVE: Although diabetic retinopathy is a leading cause of blindness worldwide, diabetes-related blindness can be prevented through effective screening, detection, and treatment of disease. The study goal was to develop risk stratification algorithms for the onset of retinal complications of diabetes, including proliferative diabetic retinopathy, referable retinopathy, and macular edema. RESEARCH DESIGN AND METHODS: Retrospective cohort analysis of patients from the Kaiser Permanente Northern California Diabetes Registry who had no evidence of diabetic retinopathy at a baseline diabetic retinopathy screening during 2008-2020 was performed. Machine learning and logistic regression prediction models for onset of proliferative diabetic retinopathy, diabetic macular edema, and referable retinopathy detected through routine screening were trained and internally validated. Model performance was assessed using area under the curve (AUC) metrics. RESULTS: The study cohort (N = 276,794) was 51.9% male and 42.1% White. Mean (±SD) age at baseline was 60.0 (±13.1) years. A machine learning XGBoost algorithm was effective in identifying patients who developed proliferative diabetic retinopathy (AUC 0.86; 95% CI, 0.86-0.87), diabetic macular edema (AUC 0.76; 95% CI, 0.75-0.77), and referable retinopathy (AUC 0.78; 95% CI, 0.78-0.79). Similar results were found using a simpler nine-covariate logistic regression model: proliferative diabetic retinopathy (AUC 0.82; 95% CI, 0.80-0.83), diabetic macular edema (AUC 0.73; 95% CI, 0.72-0.74), and referable retinopathy (AUC 0.75; 95% CI, 0.75-0.76). CONCLUSIONS: Relatively simple logistic regression models using nine readily available clinical variables can be used to rank order patients for onset of diabetic eye disease and thereby more efficiently prioritize and target screening for at risk patients.

Trends and Risk Factors for Venous Thromboembolism Among Hospitalized Medical Patients.

Importance: While hospital-associated venous thromboembolism (HA-VTE) is a known complication of hospitalization, contemporary incidence and outcomes data are scarce and methodologically contested. Objective: To define and validate an automated electronic health record (EHR)-based algorithm for retrospective detection of HA-VTE and examine contemporary HA-VTE incidence, previously reported risk factors, and outcomes. Design, Setting, and Participants: This cohort study was conducted using hospital admissions between January 1, 2013, and June 30, 2021, with follow-up until December 31, 2021. All medical (non-intensive care unit) admissions at an integrated health care delivery system with 21 hospitals in Northern California during the study period were included. Data were analyzed from January to June 2022. Exposures: Previously reported risk factors associated with HA-VTE and administration of pharmacological prophylaxis were evaluated as factors associated with HA-VTE. Main Outcomes and Measures: Yearly incidence rates and timing of HA-VTE events overall and by subtype (deep vein thrombosis, pulmonary embolism, both, or unknown), as well as readmissions and mortality rates. Results: Among 1 112 014 hospitalizations involving 529 492 patients (268 797 [50.8%] women; 75 238 Asian [14.2%], 52 697 Black [10.0%], 79 398 Hispanic [15.0%], and 307 439 non-Hispanic White [58.1%]; median [IQR] age, 67.0 [54.0-79.0] years), there were 13 843 HA-VTE events (1.2% of admissions) occurring in 10 410 patients (2.0%). HA-VTE events increased from 307 of 29 095 hospitalizations (1.1%) in the first quarter of 2013 to 551 of 33 729 hospitalizations (1.6%) in the first quarter of 2021. Among all HA-VTE events, 10 746 events (77.6%) were first noted after discharge. In multivariable analyses, several factors were associated with increased odds of HA-VTE, including active cancer (adjusted odds ratio [aOR], 1.96; 95% CI, 1.85-2.08), prior VTE (aOR, 1.71; 95% CI, 1.63-1.79), and reduced mobility (aOR, 1.63; 95% CI, 1.50-1.77). Factors associated with decreased likelihood of HA-VTE included Asian race (vs non-Hispanic White: aOR, 0.65; 95% CI, 0.61-0.69), current admission for suspected stroke (aOR, 0.73; 95% CI, 0.65-0.81), and Hispanic ethnicity (vs non-Hispanic White: aOR, 0.81; 95% CI, 0.77-0.86). HA-VTE events were associated with increased risk of readmission (hazard ratio [HR], 3.33; 95% CI, 3.25-3.41) and mortality (HR, 1.63; 95% CI, 1.57-1.70). Conclusions and Relevance: This study found that HA-VTE events occurred in 1.2% of medical admissions, increased over time, and were associated with increased adverse outcomes. These findings suggest that approaches designed to mitigate occurrence and outcomes associated with HA-VTE may remain needed.

Assessment of genetic susceptibility to multiple primary cancers through whole-exome sequencing in two large multi-ancestry studies.

BACKGROUND: Up to one of every six individuals diagnosed with one cancer will be diagnosed with a second primary cancer in their lifetime. Genetic factors contributing to the development of multiple primary cancers, beyond known cancer syndromes, have been underexplored. METHODS: To characterize genetic susceptibility to multiple cancers, we conducted a pan-cancer, whole-exome sequencing study of individuals drawn from two large multi-ancestry populations (6429 cases, 165,853 controls). We created two groupings of individuals diagnosed with multiple primary cancers: (1) an overall combined set with at least two cancers across any of 36 organ sites and (2) cancer-specific sets defined by an index cancer at one of 16 organ sites with at least 50 cases from each study population. We then investigated whether variants identified from exome sequencing were associated with these sets of multiple cancer cases in comparison to individuals with one and, separately, no cancers. RESULTS: We identified 22 variant-phenotype associations, 10 of which have not been previously discovered and were significantly overrepresented among individuals with multiple cancers, compared to those with a single cancer. CONCLUSIONS: Overall, we describe variants and genes that may play a fundamental role in the development of multiple primary cancers and improve our understanding of shared mechanisms underlying carcinogenesis.

Cross-cancer evaluation of polygenic risk scores for 16 cancer types in two large cohorts.

Even distinct cancer types share biological hallmarks. Here, we investigate polygenic risk score (PRS)-specific pleiotropy across 16 cancers in European ancestry individuals from the Genetic Epidemiology Research on Adult Health and Aging cohort (16,012 cases, 50,552 controls) and UK Biobank (48,969 cases, 359,802 controls). Within cohorts, each PRS is evaluated in multivariable logistic regression models against all other cancer types. Results are then meta-analyzed across cohorts. Ten positive and one inverse cross-cancer associations are found after multiple testing correction. Two pairs show bidirectional associations; the melanoma PRS is positively associated with oral cavity/pharyngeal cancer and vice versa, whereas the lung cancer PRS is positively associated with oral cavity/pharyngeal cancer, and the oral cavity/pharyngeal cancer PRS is inversely associated with lung cancer. Overall, we validate known, and uncover previously unreported, patterns of pleiotropy that have the potential to inform investigations of risk prediction, shared etiology, and precision cancer prevention strategies.

Pan-cancer study detects genetic risk variants and shared genetic basis in two large cohorts.

Deciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. Here, we undertake genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (408,786 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detect 21 genome-wide significant associations independent of previously reported results. Investigations of pleiotropy identify 12 cancer pairs exhibiting either positive or negative genetic correlations; 25 pleiotropic loci; and 100 independent pleiotropic variants, many of which are regulatory elements and/or influence cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.

Population-based risks for cancer in patients with ALS.

OBJECTIVE: To estimate the risks for cancer (overall and site-specific) in an amyotrophic lateral sclerosis (ALS) cohort. METHODS: In this observational longitudinal study, ALS and cancer cases were identified in a computerized Utah genealogy database (Utah Population Database) linked to a statewide cancer registry and death certificates. Hazard ratios (HRs) were estimated as the ratio of observed to expected number of cancers. Site-specific rates for cancer were estimated within the Utah Population Database; sex, birth year (5-year range), and birth state (Utah or not) cohorts were used to estimate the expected number of cancers among ALS cases. To account for an overall shortened lifespan, Cox regression was used to include years at risk in estimation of cancer risks for ALS cases. RESULTS: An overall decreased hazard (hazard ratio [HR] 0.80, p = 0.014, 95% confidence interval [CI] 0.66-0.96) was found for cancer of any site in 1,081 deceased patients with ALS. A decreased hazard was found for lung cancer (HR 0.23, p = 0.002, CI 0.05-0.63). An increased hazard was found for salivary (HR 5.27, p = 0.041, 95% CI 1.09-15.40) and testicular (HR 3.82, p = 0.042, 95% CI 1.06-9.62) cancers. A nonsignificant hazard was observed for cutaneous malignant melanoma (HR 1.62, p = 0.12, 95% CI 0.88-2.71) for which increased risk has previously been reported. CONCLUSIONS: Using a unique population database, the overall risk of cancer of any site was found to be significantly reduced in cases with ALS, as was the risk of lung cancer. Significantly increased risk was observed for salivary and testicular cancers.

ETS1 regulates the expression of ATXN2.

Spinocerebellar ataxia type 2 (SCA2) is an autosomal dominant disorder caused by the expansion of a CAG tract in the ATXN2 gene. The SCA2 phenotype is characterized by cerebellar ataxia, neuropathy and slow saccades. SCA2 foreshortens life span and is currently without symptomatic or disease-modifying treatments. Identifying function-specific therapeutics for SCA2 is problematic due to the limited knowledge of ATXN2 function. As SCA2 is likely caused by a gain-of-toxic or gain-of-normal function like other polyglutamine disorders, targeting ATXN2 expression may represent a valid therapeutic approach. This study characterized aspects of ATXN2 expression control using an ATXN2 promoter-luciferase (luc) reporter construct. We verified the fidelity of construct expression by generating transgenic mice expressing the reporter construct. High reporter expression was seen in the cerebellum and olfactory bulb in vivo but there was relatively low expression in other tissues, similar to the expression of endogenous ataxin-2. We verified the second of two possible start codons as the functional start codon in ATXN2. By evaluating deletions in the ATXN2 promoter, we identified an E-twenty six (ETS)-binding site required for ATXN2 expression. We verified that endogenous ETS1 interacted with the ATXN2 promoter by an electromobility supershift assay and chromatin immunoprecipitation polymerase chain reaction. ETS1 overexpression increased ATXN2-luc (ATXN2-luciferase) as well as endogenous ATXN2 expression. Deletion of the putative ETS1-binding site abrogated the effects on the expression of ATXN2-luc. A dominant negative ETS1 and an ETS1 short-hairpin RNA both reduced ATXN2-luc expression. Our study broadens the understanding on the transcriptional control of ATXN2 and reveals specific regulatory features of the ATXN2 promoter that can be exploited therapeutically.