Genetics of Cardiac Aging Implicate Organ-Specific Variation.

Heart structure and function change with age, and the notion that the heart may age faster for some individuals than for others has driven interest in estimating cardiac age acceleration. However, current approaches have limited feature richness (heart measurements; radiomics) or capture extraneous data and therefore lack cardiac specificity (deep learning [DL] on unmasked chest MRI). These technical limitations have been a barrier to efforts to understand genetic contributions to age acceleration. We hypothesized that a video-based DL model provided with heart-masked MRI data would capture a rich yet cardiac-specific representation of cardiac aging. In 61,691 UK Biobank participants, we excluded noncardiac pixels from cardiac MRI and trained a video-based DL model to predict age from one cardiac cycle in the 4-chamber view. We then computed cardiac age acceleration as the bias-corrected prediction of heart age minus the calendar age. Predicted heart age explained 71.1% of variance in calendar age, with a mean absolute error of 3.3 years. Cardiac age acceleration was linked to unfavorable cardiac geometry and systolic and diastolic dysfunction. We also observed links between cardiac age acceleration and diet, decreased physical activity, increased alcohol and tobacco use, and altered levels of 239 serum proteins, as well as adverse brain MRI characteristics. We found cardiac age acceleration to be heritable (h2g 26.6%); a genome-wide association study identified 8 loci related to linked to cardiomyopathy (near TTN, TNS1, LSM3, PALLD, DSP, PLEC, ANKRD1 and MYO18B) and an additional 16 loci (near MECOM, NPR3, KLHL3, HDGFL1, CDKN1A, ELN, SLC25A37, PI15, AP3M1, HMGA2, ADPRHL1, PGAP3, WNT9B, UHRF1 and DOK5). Of the discovered loci, 21 were not previously associated with cardiac age acceleration. Mendelian randomization revealed that lower genetically mediated levels of 6 circulating proteins (MSRA most strongly), as well as greater levels of 5 proteins (LXN most strongly) were associated with cardiac age acceleration, as were greater blood pressure and Lp(a). A polygenic score for cardiac age acceleration predicted earlier onset of arrhythmia, heart failure, myocardial infarction, and mortality. These findings provide a thematic understanding of cardiac age acceleration and suggest that heart- and vascular-specific factors are key to cardiac age acceleration, predominating over a more global aging program.

Selenoprotein deficiency disorder predisposes to aortic aneurysm formation.

Aortic aneurysms, which may dissect or rupture acutely and be lethal, can be a part of multisystem disorders that have a heritable basis. We report four patients with deficiency of selenocysteine-containing proteins due to selenocysteine Insertion Sequence Binding Protein 2 (SECISBP2) mutations who show early-onset, progressive, aneurysmal dilatation of the ascending aorta due to cystic medial necrosis. Zebrafish and male mice with global or vascular smooth muscle cell (VSMC)-targeted disruption of Secisbp2 respectively show similar aortopathy. Aortas from patients and animal models exhibit raised cellular reactive oxygen species, oxidative DNA damage and VSMC apoptosis. Antioxidant exposure or chelation of iron prevents oxidative damage in patient's cells and aortopathy in the zebrafish model. Our observations suggest a key role for oxidative stress and cell death, including via ferroptosis, in mediating aortic degeneration.

Assessment of valvular function in over 47,000 people using deep learning-based flow measurements.

Valvular heart disease is associated with a high global burden of disease. Even mild aortic stenosis confers increased morbidity and mortality, prompting interest in understanding normal variation in valvular function at scale. We developed a deep learning model to study velocity-encoded magnetic resonance imaging in 47,223 UK Biobank participants. We calculated eight traits, including peak velocity, mean gradient, aortic valve area, forward stroke volume, mitral and aortic regurgitant volume, greatest average velocity, and ascending aortic diameter. We then computed sex-stratified reference ranges for these phenotypes in up to 31,909 healthy individuals. In healthy individuals, we found an annual decrement of 0.03cm 2 in the aortic valve area. Participants with mitral valve prolapse had a 1 standard deviation [SD] higher mitral regurgitant volume (P=9.6 × 10 -12 ), and those with aortic stenosis had a 4.5 SD-higher mean gradient (P=1.5 × 10 -431 ), validating the derived phenotypes' associations with clinical disease. Greater levels of ApoB, triglycerides, and Lp(a) assayed nearly 10 years prior to imaging were associated with higher gradients across the aortic valve. Metabolomic profiles revealed that increased glycoprotein acetyls were also associated with an increased aortic valve mean gradient (0.92 SD, P=2.1 x 10 -22 ). Finally, velocity-derived phenotypes were risk markers for aortic and mitral valve surgery even at thresholds below what is considered relevant disease currently. Using machine learning to quantify the rich phenotypic data of the UK Biobank, we report the largest assessment of valvular function and cardiovascular disease in the general population.

Wearable accelerometer-derived physical activity and incident disease.

Physical activity is regarded as favorable to health but effects across the spectrum of human disease are poorly quantified. In contrast to self-reported measures, wearable accelerometers can provide more precise and reproducible activity quantification. Using wrist-worn accelerometry data from the UK Biobank prospective cohort study, we test associations between moderate-to-vigorous physical activity (MVPA) - both total MVPA minutes and whether MVPA is above a guideline-based threshold of ≥150 min/week-and incidence of 697 diseases using Cox proportional hazards models adjusted for age, sex, body mass index, smoking, Townsend Deprivation Index, educational attainment, diet quality, alcohol use, blood pressure, anti-hypertensive use. We correct for multiplicity at a false discovery rate of 1%. We perform analogous testing using self-reported MVPA. Among 96,244 adults wearing accelerometers for one week (age 62 ± 8 years), MVPA is associated with 373 (54%) tested diseases over a median 6.3 years of follow-up. Greater MVPA is overwhelmingly associated with lower disease risk (98% of associations) with hazard ratios (HRs) ranging 0.70-0.98 per 150 min increase in weekly MVPA, and associations spanning all 16 disease categories tested. Overall, associations with lower disease risk are enriched for cardiac (16%), digestive (14%), endocrine/metabolic (10%), and respiratory conditions (8%) (chi-square p < 0.01). Similar patterns are observed using the guideline-based threshold of ≥150 MVPA min/week. Some of the strongest associations with guideline-adherent activity include lower risks of incident heart failure (HR 0.65, 95% CI 0.55-0.77), type 2 diabetes (HR 0.64, 95% CI 0.58-0.71), cholelithiasis (HR 0.61, 95% CI 0.54-0.70), and chronic bronchitis (HR 0.42, 95% CI 0.33-0.54). When assessed within 456,374 individuals providing self-reported MVPA, effect sizes for guideline-adherent activity are substantially smaller (e.g., heart failure HR 0.84, 95% CI 0.80-0.88). Greater wearable device-based physical activity is robustly associated with lower disease incidence. Future studies are warranted to identify potential mechanisms linking physical activity and disease, and assess whether optimization of measured activity can reduce disease risk.

Hematopoietic mosaic chromosomal alterations increase the risk for diverse types of infection.

Age is the dominant risk factor for infectious diseases, but the mechanisms linking age to infectious disease risk are incompletely understood. Age-related mosaic chromosomal alterations (mCAs) detected from genotyping of blood-derived DNA, are structural somatic variants indicative of clonal hematopoiesis, and are associated with aberrant leukocyte cell counts, hematological malignancy, and mortality. Here, we show that mCAs predispose to diverse types of infections. We analyzed mCAs from 768,762 individuals without hematological cancer at the time of DNA acquisition across five biobanks. Expanded autosomal mCAs were associated with diverse incident infections (hazard ratio (HR) 1.25; 95% confidence interval (CI) = 1.15-1.36; P = 1.8 × 10-7), including sepsis (HR 2.68; 95% CI = 2.25-3.19; P = 3.1 × 10-28), pneumonia (HR 1.76; 95% CI = 1.53-2.03; P = 2.3 × 10-15), digestive system infections (HR 1.51; 95% CI = 1.32-1.73; P = 2.2 × 10-9) and genitourinary infections (HR 1.25; 95% CI = 1.11-1.41; P = 3.7 × 10-4). A genome-wide association study of expanded mCAs identified 63 loci, which were enriched at transcriptional regulatory sites for immune cells. These results suggest that mCAs are a marker of impaired immunity and confer increased predisposition to infections.

Genetics of 35 blood and urine biomarkers in the UK Biobank.

Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n = 363,228 individuals). We identify 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations and additional sets of large-effect (>0.1 s.d.) protein-altering, human leukocyte antigen (HLA) and copy number variant (CNV) associations. Through Mendelian randomization (MR) analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores (PRSs) for each biomarker and build 'multi-PRS' models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n = 135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases.

Premature Menopause, Clonal Hematopoiesis, and Coronary Artery Disease in Postmenopausal Women.

BACKGROUND: Premature menopause is an independent risk factor for cardiovascular disease in women, but mechanisms underlying this association remain unclear. Clonal hematopoiesis of indeterminate potential (CHIP), the age-related expansion of hematopoietic cells with leukemogenic mutations without detectable malignancy, is associated with accelerated atherosclerosis. Whether premature menopause is associated with CHIP is unknown. METHODS: We included postmenopausal women from the UK Biobank (n=11 495) aged 40 to 70 years with whole exome sequences and from the Women's Health Initiative (n=8111) aged 50 to 79 years with whole genome sequences. Premature menopause was defined as natural or surgical menopause occurring before age 40 years. Co-primary outcomes were the presence of any CHIP and CHIP with variant allele frequency >0.1. Logistic regression tested the association of premature menopause with CHIP, adjusted for age, race, the first 10 principal components of ancestry, smoking, diabetes, and hormone therapy use. Secondary analyses considered natural versus surgical premature menopause and gene-specific CHIP subtypes. Multivariable-adjusted Cox models tested the association between CHIP and incident coronary artery disease. RESULTS: The sample included 19 606 women, including 418 (2.1%) with natural premature menopause and 887 (4.5%) with surgical premature menopause. Across cohorts, CHIP prevalence in postmenopausal women with versus without a history of premature menopause was 8.8% versus 5.5% (P<0.001), respectively. After multivariable adjustment, premature menopause was independently associated with CHIP (all CHIP: odds ratio, 1.36 [95% 1.10-1.68]; P=0.004; CHIP with variant allele frequency >0.1: odds ratio, 1.40 [95% CI, 1.10-1.79]; P=0.007). Associations were larger for natural premature menopause (all CHIP: odds ratio, 1.73 [95% CI, 1.23-2.44]; P=0.001; CHIP with variant allele frequency >0.1: odds ratio, 1.91 [95% CI, 1.30-2.80]; P<0.001) but smaller and nonsignificant for surgical premature menopause. In gene-specific analyses, only DNMT3A CHIP was significantly associated with premature menopause. Among postmenopausal middle-aged women, CHIP was independently associated with incident coronary artery disease (hazard ratio associated with all CHIP: 1.36 [95% CI, 1.07-1.73]; P=0.012; hazard ratio associated with CHIP with variant allele frequency >0.1: 1.48 [95% CI, 1.13-1.94]; P=0.005). CONCLUSIONS: Premature menopause, especially natural premature menopause, is independently associated with CHIP among postmenopausal women. Natural premature menopause may serve as a risk signal for predilection to develop CHIP and CHIP-associated cardiovascular disease.

Hematopoietic mosaic chromosomal alterations and risk for infection among 767,891 individuals without blood cancer.

Age is the dominant risk factor for infectious diseases, but the mechanisms linking the two are incompletely understood1,2. Age-related mosaic chromosomal alterations (mCAs) detected from blood-derived DNA genotyping, are structural somatic variants associated with aberrant leukocyte cell counts, hematological malignancy, and mortality3-11. Whether mCAs represent independent risk factors for infection is unknown. Here we use genome-wide genotyping of blood DNA to show that mCAs predispose to diverse infectious diseases. We analyzed mCAs from 767,891 individuals without hematological cancer at DNA acquisition across four countries. Expanded mCA (cell fraction >10%) prevalence approached 4% by 60 years of age and was associated with diverse incident infections, including sepsis, pneumonia, and coronavirus disease 2019 (COVID-19) hospitalization. A genome-wide association study of expanded mCAs identified 63 significant loci. Germline genetic alleles associated with expanded mCAs were enriched at transcriptional regulatory sites for immune cells. Our results link mCAs with impaired immunity and predisposition to infections. Furthermore, these findings may also have important implications for the ongoing COVID-19 pandemic, particularly in prioritizing individual preventive strategies and evaluating immunization responses.

Genetic Interleukin 6 Signaling Deficiency Attenuates Cardiovascular Risk in Clonal Hematopoiesis.

BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP) refers to clonal expansion of hematopoietic stem cells attributable to acquired leukemic mutations in genes such as DNMT3A or TET2. In humans, CHIP associates with prevalent myocardial infarction. In mice, CHIP accelerates atherosclerosis and increases IL-6/IL-1ß expression, raising the hypothesis that IL-6 pathway antagonism in CHIP carriers would decrease cardiovascular disease (CVD) risk. METHODS: We analyzed exome sequences from 35 416 individuals in the UK Biobank without prevalent CVD, to identify participants with DNMT3A or TET2 CHIP. We used the IL6R p.Asp358Ala coding mutation as a genetic proxy for IL-6 inhibition. We tested the association of CHIP status with incident CVD events (myocardial infarction, coronary revascularization, stroke, or death), and whether it was modified by IL6R p.Asp358Ala. RESULTS: We identified 1079 (3.0%) individuals with CHIP, including 432 (1.2%) with large clones (allele fraction >10%). During 6.9-year median follow-up, CHIP associated with increased incident CVD event risk (hazard ratio, 1.27 [95% CI, 1.04-1.56], P=0.019), with greater risk from large CHIP clones (hazard ratio, 1.59 [95% CI, 1.21-2.09], P<0.001). IL6R p.Asp358Ala attenuated CVD event risk among participants with large CHIP clones (hazard ratio, 0.46 [95% CI, 0.29-0.73], P<0.001) but not in individuals without CHIP (hazard ratio, 0.95 [95% CI, 0.89-1.01], P=0.08; Pinteraction=0.003). In 9951 independent participants, the association of CHIP status with myocardial infarction similarly varied by IL6R p.Asp358Ala (Pinteraction=0.036). CONCLUSIONS: CHIP is associated with increased risk of incident CVD. Among carriers of large CHIP clones, genetically reduced IL-6 signaling abrogated this risk.

A novel APOB mutation identified by exome sequencing cosegregates with steatosis, liver cancer, and hypocholesterolemia.

OBJECTIVE: In familial hypobetalipoproteinemia, fatty liver is a characteristic feature, and there are several reports of associated cirrhosis and hepatocarcinoma. We investigated a large kindred in which low-density lipoprotein cholesterol, fatty liver, and hepatocarcinoma displayed an autosomal dominant pattern of inheritance. APPROACH AND RESULTS: The proband was a 25-year-old female with low plasma cholesterol and hepatic steatosis. Low plasma levels of total cholesterol and fatty liver were observed in 10 more family members; 1 member was affected by liver cirrhosis, and 4 more subjects died of either hepatocarcinoma or carcinoma on cirrhosis. To identify the causal mutation in this family, we performed exome sequencing in 2 participants with hypocholesterolemia and fatty liver. Approximately 22 400 single nucleotide variants were identified in each sample. After variant filtering, 300 novel shared variants remained. A nonsense variant, p.K2240X, attributable to an A>T mutation in exon 26 of APOB (c.6718A>T) was identified, and this variant was confirmed by Sanger sequencing. The gentotypic analysis of 16 family members in total showed that this mutation segregated with the low cholesterol trait. In addition, genotyping of the PNPLA3 p.I148M did not show significant frequency differences between carriers and noncarriers of the c.6718A>T APOB gene mutation. CONCLUSIONS: We used exome sequencing to discover a novel nonsense mutation in exon 26 of APOB (p.K2240X) responsible for low cholesterol and fatty liver in a large kindred. This mutation may also be responsible for cirrhosis and liver cancer in this family.

Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.