Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with ...88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.
We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained to predict a binary outcome ...constructed from reported suicide, suicide attempt, and overdose diagnoses with varying choices of study design and prediction methodology. Each model used twenty cross-sectional and 190 longitudinal variables observed in eight time intervals covering 7.5 years prior to the time of prediction. Ensembles of seven base models were created and fine-tuned with ten variables expected to change with study design and outcome definition in order to predict suicide and combined outcome in a prospective cohort. The ensemble models achieved c-statistics of 0.73 on 2-year suicide risk and 0.83 on the combined outcome when predicting on a prospective cohort of Formula: see text 4.2 M veterans. The ensembles rely on nonlinear base models trained using a matched retrospective nested case-control (Rcc) study cohort and show good calibration across a diversity of subgroups, including risk strata, age, sex, race, and level of healthcare utilization. In addition, a linear Rcc base model provided a rich set of biological predictors, including indicators of suicide, substance use disorder, mental health diagnoses and treatments, hypoxia and vascular damage, and demographics.
Psychiatric disorders cost an estimated $273 billion annually. This cost comes largely in the form of lost income and the chronic disability that often strikes people when they are young and can last ...decades. While the monetary costs are quantifiable, the suffering of each individual patient is no less vital. As many as 1 in 5 persons diagnosed with mental illness will commit suicide, a contributing factor in suicide being the second leading cause of death of people age 15-34. There is a critical need to find better ways to identify and help those who are at risk. Understanding mental illness and improving treatment has been difficult due to the heterogeneous and complex etiology of these illnesses. A significant challenge for the field is integrating findings from diverse laboratories all over the world contributing to the ever expanding literature and translating them into actionable treatment. Our lab employs a convergent functional genomics approach which incorporates multiple independent lines of evidence provided by genetic and functional genomic data published in the primary literature as a Bayesian strategy to prioritize experimental findings. Heritability and genetics clearly play an important role in psychiatric disorders. We looked at schizophrenia and alcoholism in separate case-control analyses in order to identify and prioritize genes related to these disorders. We were able to reproduce these findings in additional independent cohorts using polygenic risk scores. We found overlap in these disorders, and identified possible underlying biological processes. Genetics play an important role in identifying clinical risk, particularly at the population level. At the level of the individual, gene expression may provide more proximal association to disease state, assimilating environmental, genetic, as well as epigenetic influence. We undertook N of 1 analyses in a longitudinally followed cohort of psychiatric participants, identifying genes which change in expression tracking an individual’s change in suicidal ideation. These genes were able to predict suicidal behavior in independent cohorts. When combined with simple clinical instruments these predictions were improved. This work shows how multi-level integration of genetic, gene expression, and clinical data could be used to enable precision medicine in psychiatry.
Uric acid may mediate aspects of the relationship between hypertension and kidney disease via renal vasoconstriction and systemic hypertension. To investigate the relationship between uric acid and ...subsequent reduced kidney function, limited-access data of 13,338 participants with intact kidney function in two community-based cohorts, the Atherosclerosis Risks in Communities and the Cardiovascular Health Study, were pooled. Mean baseline serum uric acid was 5.9 +/- 1.5 mg/dl, mean baseline serum creatinine was 0.9 +/- 0.2 mg/dl, and mean baseline estimated GFR was 90.4 +/- 19.4 ml/min/1.73 m(2). During 8.5 +/- 0.9 yr of follow-up, 712 (5.6%) had incident kidney disease defined by GFR decrease (>or=15 ml/min/1.73 m(2) with final GFR <60 ml/min/1.73 m(2)), while 302 (2.3%) individuals had incident kidney disease defined by creatinine increase (>or=0.4 mg/dl with final serum creatinine >1.4 mg/dl in men and 1.2 mg/dl in women). In GFR- and creatinine-based logistic regression models, baseline uric acid level was associated with increased risk for incident kidney disease (odds ratio 1.07 95% confidence interval 1.01 to 1.14 and 1.11 95% confidence interval 1.02 to 1.21 per 1-mg/dl increase in uric acid, respectively), after adjustment for age, gender, race, diabetes, systolic BP, hypertension, cardiovascular disease, left ventricular hypertrophy, smoking, alcohol use, education, lipids, albumin, hematocrit, baseline kidney function and cohort; therefore, elevated serum uric acid level is a modest, independent risk factor for incident kidney disease in the general population.
The Framingham Predictive Instrument in Chronic Kidney Disease Daniel E. Weiner, Hocine Tighiouart, Essam F. Elsayed, John L. Griffith, Deeb N. Salem, Andrew S. Levey, Mark J. Sarnak In order to ...determine the utility of the Framingham equations in individuals with chronic kidney disease (CKD), we pooled individuals without pre-existing coronary disease age 45 to 74 years from the ARIC (Atherosclerosis Risk In Communities) and CHS (Cardiovascular Health Study) trials with CKD. Chronic kidney disease was defined by estimated glomerular filtration rate of 15 to 60 ml/min/1.73 m2 . Discrimination was inferior to that seen in the non-CKD population, and calibration was also poor, with Framingham scores generally underpredicting events in individuals with CKD at 5 and 10 years. Discrimination was improved by refitting models with population-specific coefficients, while recalibration improved prediction in women. Development of CKD-specific equations is needed.
Background Chronic kidney disease (CKD) and obesity are important public health concerns. We examined the association between anthropomorphic measures and incident CKD and mortality. Study Design ...Cohort study. Setting & Participants Individual patient data pooled from the Atherosclerosis Risk in Communities Study and the Cardiovascular Health Study. Predictors Waist-to-hip ratio (WHR), body mass index (BMI). Outcomes & Measurements Incident CKD defined as serum creatinine level increase greater than 0.4 mg/dL with baseline creatinine level of 1.4 mg/dL or less in men and 1.2 mg/dL or less in women and final creatinine level greater than these levels, and, in separate analyses, estimated glomerular filtration rate (eGFR) decrease of 15 mL/min/1.73 m2 or greater with baseline eGFR of 60 mL/min/1.73 m2 or greater and final eGFR less than 60 mL/min/1.73 m2 . Multivariable logistic regression to determine the association between WHR, BMI, and outcomes. Cox models to evaluate a secondary composite outcome of all-cause mortality and incident CKD. Results Of 13,324 individuals, mean WHR was 0.96 in men and 0.89 in women and mean BMI was 27.2 kg/m2 in both men and women. During 9.3 years, 300 patients (2.3%) in creatinine-based models and 710 patients (5.5%) in eGFR-based models developed CKD. In creatinine-based models, each SD increase in WHR was associated with increased risk of incident CKD (odds ratio, 1.22; 95% confidence interval CI, 1.05 to 1.43) and the composite outcome (hazard ratio, 1.12; 95% CI, 1.06 to 1.18), whereas each SD increase in BMI was not associated with CKD (odds ratio, 1.05; 95% CI, 0.93 to 1.20) and appeared protective for the composite outcome (hazard ratio, 0.94; 95% CI, 0.90 to 0.99). Results of eGFR-based models were similar. Limitations Single measures of creatinine, no albuminuria data. Conclusions WHR, but not BMI, is associated with incident CKD and mortality. Assessment of CKD risk should use WHR rather than BMI as an anthropomorphic measure of obesity.
Background Albuminuria, a kidney marker of microvascular disease, may herald microvascular disease elsewhere, including in the brain. Study Design Cross sectional. Setting & Participants Boston, MA, ...elders receiving home health services to maintain independent living who consented to brain magnetic resonance imaging. Predictor Urine albumin-creatinine ratio (ACR). Outcome Performance on a cognitive battery assessing executive function and memory by using principal components analysis and white matter hyperintensity volume on brain imaging, evaluated in logistic and linear regression models. Results In 335 participants, mean age was 73.4 ± 8.1 years and 123 participants had microalbuminuria or macroalbuminuria. Each doubling of ACR was associated with worse executive function (β = −0.05; P = 0.005 in univariate and β = −0.07; P = 0.004 in multivariable analyses controlling for age, sex, race, education, diabetes, cardiovascular disease, hypertension, medications, and estimated glomerular filtration rate eGFR), but not with worse memory or working memory. Individuals with microalbuminuria or macroalbuminuria were more likely to be in the lower versus the highest tertile of executive functioning (odds ratio, 1.18; 95% confidence interval, 1.06 to 1.32; odds ratio, 1.19; 95% confidence interval, 1.05 to 1.35 per doubling of ACR in univariate and multivariable analyses, respectively). Albuminuria was associated with qualitative white matter hyperintensity grade (odds ratio, 1.13; 95% confidence interval, 1.02 to 1.25; odds ratio, 1.15; 95% confidence interval, 1.02 to 1.29 per doubling of ACR) in univariate and multivariable analyses and with quantitative white matter hyperintensity volume (β = 0.11; P = 0.007; β = 0.10; P = 0.01) in univariate and multivariable analyses of log-transformed data. Results were similar when excluding individuals with macroalbuminuria. Limitations Single measurement of ACR, indirect creatinine calibration, and reliance on participant recall for elements of medical history. Conclusions Albuminuria is associated with worse cognitive performance, particularly in executive functioning, as well as increased white matter hyperintensity volume. Albuminuria likely identifies greater brain microvascular disease burden.
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