Aniruddh P. Patel

Endocrine tumors such as aldosterone-producing adrenal adenomas (APAs), a cause of severe hypertension, feature constitutive hormone production and unrestrained cell proliferation; the mechanisms linking these events are unknown. We identify two recurrent somatic mutations in and near the selectivity filter of the potassium (K(+)) channel KCNJ5 that are present in 8 of 22 human APAs studied. Both produce increased sodium (Na(+)) conductance and cell depolarization, which in adrenal glomerulosa cells produces calcium (Ca(2+)) entry, the signal for aldosterone production and cell proliferation. Similarly, we identify an inherited KCNJ5 mutation that produces increased Na(+) conductance in a Mendelian form of severe aldosteronism and massive bilateral adrenal hyperplasia. These findings explain pathogenesis in a subset of patients with severe hypertension and implicate loss of K(+) channel selectivity in constitutive cell proliferation and hormone production.

OBJECTIVE: Lp(a) (lipoprotein[a]) concentrations are associated with atherosclerotic cardiovascular disease (ASCVD), and new therapies that enable potent and specific reduction are in development. In the largest study conducted to date, we address 3 areas of uncertainty: (1) the magnitude and shape of ASCVD risk conferred across the distribution of lipoprotein(a) concentrations; (2) variation of risk across racial and clinical subgroups; (3) clinical importance of a high lipoprotein(a) threshold to guide therapy. Approach and Results: Relationship of lipoprotein(a) to incident ASCVD was studied in 460 506 middle-aged UK Biobank participants. Over a median follow-up of 11.2 years, incident ASCVD occurred in 22 401 (4.9%) participants. Median lipoprotein(a) concentration was 19.6 nmol/L (25th-75th percentile 7.6-74.8). The relationship between lipoprotein(a) and ASCVD appeared linear across the distribution, with a hazard ratio of 1.11 (95% CI, 1.10-1.12) per 50 nmol/L increment. Substantial differences in concentrations were noted according to race-median values for white, South Asian, black, and Chinese individuals were 19, 31, 75, and 16 nmol/L, respectively. However, risk per 50 nmol/L appeared similar-hazard ratios of 1.11, 1.10, and 1.07 for white, South Asian, and black individuals, respectively. A high lipoprotein(a) concentration defined as ≥150 nmol/L was present in 12.2% of those without and 20.3% of those with preexisting ASCVD and associated with hazard ratios of 1.50 (95% CI, 1.44-1.56) and 1.16 (95% CI, 1.05-1.27), respectively. CONCLUSIONS: Lipoprotein(a) concentrations predict incident ASCVD among middle-aged adults within primary and secondary prevention contexts, with a linear risk gradient across the distribution. Concentrations are variable across racial subgroups, but the associated risk appears similar.

Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions - familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background - the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.

Abstract Identification of individuals at highest risk of coronary artery disease (CAD)—ideally before onset—remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPS Mult , that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPS Mult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10–2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPS Mult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70–1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPS Mult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPS Mult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.