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BACKGROUND - Observations from statin clinical trials and from Mendelian randomization studies suggest that low low-density lipoprotein cholesterol (LDL-C) concentrations may be associated with increased risk of type 2 diabetes mellitus (T2DM). Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations in increased risk of T2DM.
METHODS AND FINDINGS - We used de-identified electronic health records (EHRs) at Vanderbilt University Medical Center to compare the risk of T2DM in a cross-sectional study among individuals with very low (≤60 mg/dl, N = 8,943) and normal (90-130 mg/dl, N = 71,343) LDL-C levels calculated using the Friedewald formula. LDL-C levels associated with statin use, hospitalization, or a serum albumin level < 3 g/dl were excluded. We used a 2-phase approach: in 1/3 of the sample (discovery) we used T2DM phenome-wide association study codes (phecodes) to identify cases and controls, and in the remaining 2/3 (validation) we identified T2DM cases and controls using a validated algorithm. The analysis plan for the validation phase was constructed at the time of the design of that component of the study. The prevalence of T2DM in the very low and normal LDL-C groups was compared using logistic regression with adjustment for age, race, sex, body mass index (BMI), high-density lipoprotein cholesterol, triglycerides, and duration of care. Secondary analyses included prespecified stratification by sex, race, BMI, and LDL-C level. In the discovery cohort, phecodes related to T2DM were significantly more frequent in the very low LDL-C group. In the validation cohort (N = 33,039 after applying the T2DM algorithm to identify cases and controls), the risk of T2DM was increased in the very low compared to normal LDL-C group (odds ratio [OR] 2.06, 95% CI 1.80-2.37; P < 2 × 10-16). The findings remained significant in sensitivity analyses. The association between low LDL-C levels and T2DM was significant in males (OR 2.43, 95% CI 2.00-2.95; P < 2 × 10-16) and females (OR 1.74, 95% CI 1.42-2.12; P = 6.88 × 10-8); in normal weight (OR 2.18, 95% CI 1.59-2.98; P = 1.1× 10-6), overweight (OR 2.17, 95% CI 1.65-2.83; P = 1.73× 10-8), and obese (OR 2.00, 95% CI 1.65-2.41; P = 8 × 10-13) categories; and in individuals with LDL-C < 40 mg/dl (OR 2.31, 95% CI 1.71-3.10; P = 3.01× 10-8) and LDL-C 40-60 mg/dl (OR 1.99, 95% CI 1.71-2.32; P < 2.0× 10-16). The association was significant in individuals of European ancestry (OR 2.67, 95% CI 2.25-3.17; P < 2 × 10-16) but not in those of African ancestry (OR 1.09, 95% CI 0.81-1.46; P = 0.56). A limitation was that we only compared groups with very low and normal LDL-C levels; also, since this was not an inception cohort, we cannot exclude the possibility of reverse causation.
CONCLUSIONS - Very low LDL-C concentrations occurring in the absence of statin treatment were significantly associated with T2DM risk in a large EHR population; this increased risk was present in both sexes and all BMI categories, and in individuals of European ancestry but not of African ancestry. Longitudinal cohort studies to assess the relationship between very low LDL-C levels not associated with lipid-lowering therapy and risk of developing T2DM will be important.

OBJECTIVE - Hepatorenal Syndrome (HRS) is a devastating form of acute kidney injury (AKI) in advanced liver disease patients with high morbidity and mortality, but phenotyping algorithms have not yet been developed using large electronic health record (EHR) databases. We evaluated and compared multiple phenotyping methods to achieve an accurate algorithm for HRS identification.
MATERIALS AND METHODS - A national retrospective cohort of patients with cirrhosis and AKI admitted to 124 Veterans Affairs hospitals was assembled from electronic health record data collected from 2005 to 2013. AKI was defined by the Kidney Disease: Improving Global Outcomes criteria. Five hundred and four hospitalizations were selected for manual chart review and served as the gold standard. Electronic Health Record based predictors were identified using structured and free text clinical data, subjected through NLP from the clinical Text Analysis Knowledge Extraction System. We explored several dimension reduction techniques for the NLP data, including newer high-throughput phenotyping and word embedding methods, and ascertained their effectiveness in identifying the phenotype without structured predictor variables. With the combined structured and NLP variables, we analyzed five phenotyping algorithms: penalized logistic regression, naïve Bayes, support vector machines, random forest, and gradient boosting. Calibration and discrimination metrics were calculated using 100 bootstrap iterations. In the final model, we report odds ratios and 95% confidence intervals.
RESULTS - The area under the receiver operating characteristic curve (AUC) for the different models ranged from 0.73 to 0.93; with penalized logistic regression having the best discriminatory performance. Calibration for logistic regression was modest, but gradient boosting and support vector machines were superior. NLP identified 6985 variables; a priori variable selection performed similarly to dimensionality reduction using high-throughput phenotyping and semantic similarity informed clustering (AUC of 0.81 - 0.82).
CONCLUSION - This study demonstrated improved phenotyping of a challenging AKI etiology, HRS, over ICD-9 coding. We also compared performance among multiple approaches to EHR-derived phenotyping, and found similar results between methods. Lastly, we showed that automated NLP dimension reduction is viable for acute illness.
Copyright © 2018 Elsevier Inc. All rights reserved.

Few prospective studies, and none in Asians, have systematically evaluated the relationship between blood metabolites and colorectal cancer risk. We conducted a nested case-control study to search for risk-associated metabolite biomarkers for colorectal cancer in an Asian population using blood samples collected prior to cancer diagnosis. Conditional logistic regression was performed to assess associations of metabolites with cancer risk. In this study, we included 250 incident cases with colorectal cancer and individually matched controls nested within two prospective Shanghai cohorts. We found 35 metabolites associated with risk of colorectal cancer after adjusting for multiple comparisons. Among them, 12 metabolites were glycerophospholipids including nine associated with reduced risk of colorectal cancer and three with increased risk [odds ratios per standard deviation increase of transformed metabolites: 0.31-1.98; p values: 0.002-1.25 × 10 ]. The other 23 metabolites associated with colorectal cancer risk included nine lipids other than glycerophospholipid, seven aromatic compounds, five organic acids and four other organic compounds. After mutual adjustment, nine metabolites remained statistically significant for colorectal cancer. Together, these independently associated metabolites can separate cancer cases from controls with an area under the curve of 0.76 for colorectal cancer. We have identified that dysregulation of glycerophospholipids may contribute to risk of colorectal cancer.
© 2018 UICC.

Circulating vitamin B6 levels have been found to be inversely associated with lung cancer. Most studies have focused on the B6 form pyridoxal 5'-phosphate (PLP), a direct biomarker influenced by inflammation and other factors. Using a functional B6 marker allows further investigation of the potential role of vitamin B6 status in the pathogenesis of lung cancer. We prospectively evaluated the association of the functional marker of vitamin B6 status, the 3-hydroxykynurenine:xanthurenic acid (HK:XA) ratio, with risk of lung cancer in a nested case-control study consisting of 5,364 matched case-control pairs from the Lung Cancer Cohort Consortium (LC3). We used conditional logistic regression to evaluate the association between HK:XA and lung cancer, and random effect models to combine results from different cohorts and regions. High levels of HK:XA, indicating impaired functional B6 status, were associated with an increased risk of lung cancer, the odds ratio comparing the fourth and the first quartiles (OR ) was 1.25 (95% confidence interval, 1.10-1.41). Stratified analyses indicated that this association was primarily driven by cases diagnosed with squamous cell carcinoma. Notably, the risk associated with HK:XA was approximately 50% higher in groups with a high relative frequency of squamous cell carcinoma, i.e., men, former and current smokers. This risk of squamous cell carcinoma was present in both men and women regardless of smoking status.
© 2017 UICC.

OBJECTIVE - To evaluate the relationship between genetic ancestry and uterine fibroid characteristics.
DESIGN - Cross-sectional study.
SETTING - Not applicable.
PATIENT(S) - A total of 609 African American participants with image- or surgery-confirmed fibroids in a biorepository at Vanderbilt University electronic health record biorepository and the Coronary Artery Risk Development in Young Adults studies were included.
INTERVENTION(S) - None.
MAIN OUTCOME MEASURE(S) - Outcome measures include fibroid number (single vs. multiple), volume of largest fibroid, and largest fibroid dimension of all fibroid measurements.
RESULT(S) - Global ancestry meta-analyses revealed a significant inverse association between percentage of European ancestry and risk of multiple fibroids (odds ratio: 0.78; 95% confidence interval 0.66, 0.93; P=6.05 × 10). Local ancestry meta-analyses revealed five suggestive (P<4.80 × 10) admixture mapping peaks in 2q14.3-2q21.1, 3p14.2-3p14.1, 7q32.2-7q33, 10q21.1, 14q24.2-14q24.3, for number of fibroids and one suggestive admixture mapping peak (P<1.97 × 10) in 10q24.1-10q24.32 for volume of largest fibroid. Single variant association meta-analyses of the strongest associated region from admixture mapping of fibroid number (10q21.1) revealed a strong association at single nucleotide polymorphism variant rs12219990 (odds ratio: 0.41; 95% confidence interval 0.28, 0.60; P=3.82 × 10) that was significant after correction for multiple testing.
CONCLUSION(S) - Increasing African ancestry is associated with multiple fibroids but not with fibroid size. Local ancestry analyses identified several novel genomic regions not previously associated with fibroid number and increasing volume. Future studies are needed to explore the genetic impact that ancestry plays into the development of fibroid characteristics.
Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

BACKGROUND AND AIMS - Most familial hypercholesterolemia (FH) patients remain undertreated, and it is unclear what role health disparities may play for FH patients in the US. We sought to describe sex and racial/ethnic disparities in a national registry of US FH patients.
METHODS - We analyzed data from 3167 adults enrolled in the CAscade SCreening for Awareness and DEtection of Familial Hypercholesterolemia (CASCADE-FH) registry. Logistic regression was used to evaluate for disparities in LDL-C goals and statin use, with adjustments for covariates including age, cardiovascular risk factors, and statin intolerance.
RESULTS - In adjusted analyses, women were less likely than men to achieve treated LDL-C of <100 mg/dL (OR 0.68, 95% CI, 0.57-0.82) or ≥50% reduction from pretreatment LDL-C (OR 0.79, 95% CI, 0.65-0.96). Women were less likely than men to receive statin therapy (OR, 0.60, 95% CI, 0.50-0.73) and less likely to receive a high-intensity statin (OR, 0.60, 95% CI, 0.49-0.72). LDL-C goal achievement also varied by race/ethnicity: compared with whites, Asians and blacks were less likely to achieve LDL-C levels <100 mg/dL (Asians, OR, 0.47, 95% CI, 0.24-0.94; blacks, OR, 0.49, 95% CI, 0.32-0.74) or ≥50% reduction from pretreatment LDL-C (Asians, OR 0.56, 95% CI, 0.32-0.98; blacks, OR 0.62, 95% CI, 0.43-0.90).
CONCLUSIONS - In a contemporary US population of FH patients, we identified differences in LDL-C goal attainment and statin usage after stratifying the population by either sex or race/ethnicity. Our findings suggest that health disparities contribute to the undertreatment of US FH patients. Increased efforts are warranted to raise awareness of these disparities.
Copyright © 2017 Elsevier B.V. All rights reserved.

OBJECTIVE - Excess deposition of fat within and around vital organs and nonadipose tissues is hypothesized to contribute to cardiovascular disease (CVD) risk. We evaluated the association of abdominal intermuscular adipose tissue (IMAT) volume with coronary artery calcification in the CARDIA study (Coronary Artery Risk Development in Young Adults) participants.
APPROACH AND RESULTS - We measured IMAT in the abdominal muscles, visceral adipose tissue and pericardial adipose tissue, and coronary artery calcification using computed tomography in 3051 CARDIA participants (56% women) at the CARDIA year 25 examination (2010-2011). Mean IMAT volume and mean IMAT/total muscle volume (IMAT normalized for muscle size) were calculated in a 10-mm block of slices centered at L3-L4. Multivariable analyses included potential confounders and traditional cardiovascular disease risk factors. Compared with the lowest quartile, the upper quartile of abdominal IMAT volume was associated with higher coronary artery calcification prevalence (odds ratio [95% confidence interval], 1.6 [1.2-2.1]) after adjusting for cardiovascular disease risk factors. Results were similar for highest versus lowest quartile of IMAT normalized to total muscle volume (odds ratio [95% confidence interval], 1.5 [1.1-2.0]). Significant associations of higher IMAT and normalized IMAT with coronary artery calcification prevalence persisted when body mass index, visceral adipose tissue, or pericardial adipose tissue were added to the models.
CONCLUSIONS - In a large, community-based, cross-sectional study, we found that higher abdominal skeletal muscle adipose tissue volume was associated with subclinical atherosclerosis independent of traditional cardiovascular disease risk factors and other adipose depots.
© 2017 American Heart Association, Inc.

It is unclear whether genetic markers interact with risk factors to influence atrial fibrillation (AF) risk. We performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index in the AFGen Consortium. Study-specific results were combined using meta-analysis (88,383 individuals of European descent, including 7,292 with AF). Variants with nominal interaction associations in the discovery analysis were tested for association in four independent studies (131,441 individuals, including 5,722 with AF). In the discovery analysis, the AF risk associated with the minor rs6817105 allele (at the PITX2 locus) was greater among subjects ≤ 65 years of age than among those > 65 years (interaction p-value = 4.0 × 10). The interaction p-value exceeded genome-wide significance in combined discovery and replication analyses (interaction p-value = 1.7 × 10). We observed one genome-wide significant interaction with body mass index and several suggestive interactions with age, sex, and body mass index in the discovery analysis. However, none was replicated in the independent sample. Our findings suggest that the pathogenesis of AF may differ according to age in individuals of European descent, but we did not observe evidence of statistically significant genetic interactions with sex, body mass index, or hypertension on AF risk.

This study evaluates the relationship between single nucleotide polymorphisms (SNPs) in nonsteroidal anti-inflammatory drug (NSAID) metabolism and related pathways and spontaneous abortion (SAB, gestation < 20 weeks) risk. Women were enrolled in Right from the Start (2004-2010) prospective cohort. Periconceptional NSAIDs reported through the sixth week of pregnancy were obtained from study interviews. We evaluated 201 SNPs in 600 European American women. Interaction analyses between NSAID use and SNPs were conducted using logistic regression, adjusted for confounders. We also evaluated prostaglandin E2 urinary metabolite (PGE-M) in an independent population for association with SNPs using linear regression. NSAID use was reported by 63% of cases and 62% controls. The most significant interaction was at prostacyclin synthase (PGIS) rs5602 (OR = 0.34, 95% CI 0.19-0.60, p = 2.45 × 10) and was significant after a Bonferroni correction. NSAID users were protected from SAB (OR = 0.78, 95% CI 0.56-1.10), while non-NSAID users were at increased risk (OR = 2.11, 95% CI 1.35-3.29) in rs5602 stratified analyses. rs5602 also associated with increased PGE-M levels (Beta = 0.09, 95% CI -0.002-0.19, p = 0.033). We identified an association between a PGIS variant and SAB risk that is modified by NSAIDs use during pregnancy and directly associated with increased levels of PGE metabolites. This suggests the potential use of genetic information to guide pharmaceutical intervention to prevent adverse pregnancy outcomes.

The cyclooxygenase 2 (COX-2) pathway is upregulated in many pancreatic cancer cells, and it is believed that carcinogenetic effects of COX-2 upregulation are largely through prostaglandin E2 (PGE2) overproduction. We tested this hypothesis by evaluating the association between urinary PGE2 metabolites (PGE-M), a biomarker of in vivo PGE2 overproduction, and pancreatic cancer risk. We conducted a case-control study with 722 subjects (239 cases and 483 controls) nested within two prospective cohort studies, the Shanghai Women's Health Study (SWHS) and Shanghai Men's Health Study (SMHS). Pre-diagnosis urine samples were measured for PGE-M using a liquid chromatography/tandem mass spectrometric method. Conditional logistic regression was used to estimate odds ratio (OR) and 95% confidence intervals (95%CI), with adjustment for potential confounders. Compared to those with the lowest urine level of PGE-M (the first quartile), individuals with higher urine levels of PGE-M had an increased risk of developing pancreatic cancer, with adjusted ORs (95%CI) of 1.63 (0.98-2.73), 1.55 (0.90-2.69) and 1.94 (1.07-3.51), for the second to the fourth quartile groups, respectively (p for trend = 0.054). This dose-response positive association was more evident among those who had BMI <25 kg/m than overweight individuals (p for interaction = 0.058). After excluding cases diagnosed in the first year of follow-up and their matched controls, this positive association persisted (p for trend = 0.037) and the interaction became statistically significant (p for interaction = 0.017). Our study adds additional evidence that the COX-2 pathway is involved in pancreatic carcinogenesis and suggests that urinary PGE-M may serve as a biomarker for predicting pancreatic cancer risk.
© 2017 UICC.