98 research outputs found

    āŠļāŦāŠĩāŠūāŠŪāŠŋāŠĻāŠūāŠ°āŠūāŠŊāŠĢ āŠļāŠ‚āŠŠāŦāŠ°āŠĶāŠūāŠŊāŠĻāŠū āŠĪāŠĪāŦāŠĩāŠœāŦāŠžāŠūāŠĻ āŠĶāŦāŠĩāŠūāŠ°āŠū āŠ­āŠūāŠ°āŠĪāŦ€āŠŊ āŠ‰āŠĶāŦāŠŊāŦ‹āŠ—āŠ•āŠ°āŦāŠĪāŠūāŠ“āŠĻāŦ€ āŠļāŠ‚āŠšāŠūāŠēāŠ•āŦ€āŠŊ āŠļāŠŪāŠļāŦāŠŊāŠūāŠ“āŠĻāŠū āŠ‰āŠ•āŦ‡āŠēāŠĻāŦ‹ āŠ…āŠ­āŦāŠŊāŠūāŠļ

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    āŠ­āŠūāŠ°āŠĪ āŠļāŦŒāŠĨāŦ€ āŠŠāŦāŠ°āŠūāŠšāŦ€āŠĻ āŠ…āŠĻāŦ‡ āŠĩāŦˆāŠĶāŠŋāŠ• āŠļāŠ‚āŠļāŦāŠ•āŦƒāŠĪāŠŋ āŠ…āŠĻāŦ‡ āŠĩāŠŋāŠšāŠūāŠ°āŠ§āŠūāŠ°āŠū āŠ§āŠ°āŠūāŠĩāŠĪāŦāŠ‚ āŠļāŦāŠļāŠ‚āŠļāŦāŠ•āŦƒāŠĪ āŠ°āŠūāŠ·āŦāŠŸāŦāŠ° āŠ›āŦ‡. āŠļāŦŒ āŠŠāŦāŠ°āŠĨāŠŪ āŠ­āŠūāŠ°āŠĪāŦ‡ āŠļāŠŪāŠ—āŦāŠ° āŠĩāŠŋāŠķāŦāŠ°āŦāŠĩāŠĻāŦ‡ āŠŪāŠūāŠĻāŠĩāŠœāŦ€āŠĩāŠĻāŠĻāŦ€ āŠķāŠ°āŦ‚āŠ†āŠĪāŠŪāŠūāŠ‚ āŠļāŠ‚āŠļāŦāŠ•āŠūāŠ°āŦ€āŠĪāŠū āŠ…āŠĻāŦ‡ āŠķāŦāŠ°āŦ‡āŠ·āŦāŠ āŠĪāŠŪ āŠĩāŠŋāŠšāŠūāŠ°āŦ‹āŠĻāŦ€ āŠ°āŠœāŦ‚āŠ†āŠĪ āŠ†āŠŠāŦ€. āŠŪāŠ°āŦāŠŊāŠūāŠĶāŠŋāŠĪ āŠĩāŦāŠŊāŠūāŠŠāŠūāŠ°āŠ•āŦāŠ·āŦ‡āŠĪāŦāŠ°āŠŪāŠūāŠ‚āŠĨāŦ€ āŠ‰āŠĪāŦāŠĪāŠ°āŦ‹āŠĪāŦāŠĪāŠ° āŠŽāŦāŠ°āŠŋāŠŸāŦ€āŠķ āŠķāŠūāŠļāŠ•āŦ‹āŠĻāŠū āŠĻāŦ‡āŠœāŠū āŠĻāŦ€āŠšāŦ‡ āŠĩāŠŋāŠķāŠūāŠģāŠŠāŠūāŠŊāŠū āŠŠāŠ° āŠ‰āŠĪāŦāŠŠāŠūāŠĶāŠĻ āŠ–āŠ°āŦ€āŠĶ-āŠĩāŦ‡āŠ‚āŠšāŠūāŠĢ āŠ…āŠĻāŦ‡ āŠļāŠ‚āŠšāŠūāŠēāŠ•āŠŋāŠŊ āŠ•āŠūāŠŪāŠ—āŦ€āŠ°āŦ€ āŠ…āŠļāŦāŠĪāŠŋāŠĪāŦāŠĩāŠŪāŠūāŠ‚ āŠ†āŠĩāŦ€. āŠĪāŦ‡āŠŪāŠœ āŠŽāŦāŠ°āŠŋāŠŸāŦ€āŠķ āŠķāŠūāŠļāŠ•āŦ‹āŠĻāŠū āŠķāŠūāŠļāŠĻāŠŪāŠūāŠ‚ āŠ­āŠūāŠ°āŠĪāŠĻāŦ€ āŠ†āŠ°āŦāŠĨāŠŋāŠ•, āŠļāŠūāŠŪāŠūāŠœāŠŋāŠ•, āŠ°āŠūāŠœāŠ•āŠŋāŠŊ āŠŠāŠ°āŠŋāŠļāŦāŠĨāŠŋāŠĪāŠŋ āŠĩāŠ§āŦ āŠĩāŠŋāŠ•āŠŸ āŠŽāŠĻāŦ€ āŠ…āŠĻāŦ‡ āŠ”āŠĶāŦāŠŊāŦ‹āŠ—āŠŋāŠ• āŠ•āŦāŠ°āŠūāŠ‚āŠĪāŠŋāŠĻāŠū āŠŪāŠ‚āŠĄāŠūāŠĢ āŠĨāŠĪāŠū āŠ—āŦƒāŠđāŠ‰āŠĶāŦāŠŊāŦ‹āŠ—āŦ‹ āŠ…āŠĻāŦ‡ āŠĻāŠūāŠĻāŠūāŠŠāŠūāŠŊāŠūāŠĻāŠū āŠ§āŠ‚āŠ§āŠū-āŠ‰āŠĶāŦāŠŊāŦ‹āŠ—āŦ‹āŠĻāŦ‹ āŠ°āŠ•āŠūāŠļ āŠĨāŠŊāŦ‹. āŠ†āŠāŠūāŠĶāŦ€ āŠŠāŠ›āŦ€ āŠŠāŠĢ āŠ­āŠūāŠ°āŠĪāŠŪāŠūāŠ‚ āŠŠāŠ°āŠĶāŦ‡āŠķāŦ€ āŠĩāŠŋāŠšāŠūāŠ°āŠ§āŠūāŠ°āŠū āŠ…āŠŪāŠēāŠŪāŠūāŠ‚ āŠ°āŠđāŦ‡āŠĪāŠū āŠ­āŠūāŠ°āŠĪ āŠĶāŦ‡āŠķāŦ‡ āŠĩāŠŋāŠ•āŠūāŠļ āŠĪāŦ‹ āŠ•āŠ°āŦāŠŊāŦ‹ āŠĪāŦ‡āŠĻāŦ€ āŠļāŠūāŠĨāŦ‡ āŠ…āŠŪāŦ‡āŠ°āŠŋāŠ•āŠĻ āŠļāŠ‚āŠšāŠūāŠēāŠĻ āŠĩāŠŋāŠšāŠūāŠ°āŠ§āŠūāŠ°āŠū āŠ…āŠĻāŦ‡ āŠœāŠūāŠŠāŠūāŠĻāŦ€āŠ āŠļāŠ‚āŠšāŠūāŠēāŠĻ āŠĩāŠŋāŠšāŠūāŠ°āŠ§āŠūāŠ°āŠū āŠœāŦ‡āŠĩāŦ€ āŠĩāŠŋāŠĶāŦ‡āŠķāŦ€ āŠĩāŠŋāŠšāŠūāŠ°āŠ§āŠūāŠ°āŠūāŠĻāŦ‹ āŠĩāŠŋāŠ•āŠūāŠļ āŠĨāŠŊāŦ‹, āŠŠāŠ°āŠ‚āŠĪāŦ āŠļāŦŒāŠĨāŦ€ āŠŪāŦ‹āŠŸāŦ€ āŠļāŠŪāŠļāŦāŠŊāŠūāŠ āŠĨāŠˆ āŠ•āŦ‡ āŠ†āŠŠāŠĢāŠū āŠŪāŦ‚āŠēāŦāŠŊāŦ‹, āŠļāŠŋāŠ§āŦāŠ§āŠūāŠ‚āŠĪāŦ‹, āŠ°āŦ€āŠĪāŠŋāŠĻāŦ€āŠĪāŠŋ āŠĩāŠ—āŦ‡āŠ°āŦ‡āŠŪāŠūāŠ‚ āŠŪāŦāŠģ āŠĩāŦˆāŠĶāŠŋāŠ•āŠŪāŦ‚āŠēāŦāŠŊāŦ‹ āŠ…āŠĻāŦ‡ āŠļāŠ‚āŠļāŦāŠ•āŠūāŠ°āŦ€āŠĪāŠū āŠŠāŠĄāŦ€ āŠđāŠĪāŦ€. āŠœāŦāŠŊāŠūāŠ°āŦ‡ āŠŠāŠ°āŠĶāŦ‡āŠķāŦ€ āŠĩāŠŋāŠšāŠūāŠ°āŠ§āŠūāŠ°āŠū āŠļāŠūāŠĨāŦ‡ āŠĪāŦ‡āŠĻāŦ‹ āŠļāŦāŠŪāŦ‡āŠģ āŠĻ āŠđāŠĪāŦ‹. āŠŠāŠ°āŦ€āŠĢāŠūāŠŪāŦ‡ āŠ†āŠĩāŦ€ āŠĩāŠŋāŠ·āŠŪ āŠŠāŠ°āŠŋāŠļāŦāŠĨāŠŋāŠĪāŠŋ āŠļāŠ°āŦāŠœāŠūāŠĪāŠū āŠ§āŠ‚āŠ§āŠūāŠ•āŦ€āŠŊ āŠŠāŠ°āŦāŠŊāŠūāŠĩāŠ°āŠĢāŠĻāŦ‡ āŠŠāŠ°āŠĶāŦ‡āŠķāŦ€ āŠĩāŠŋāŠšāŠūāŠ°āŠ§āŠūāŠ°āŠū āŠŪāŠūāŠŦāŦāŠ• āŠĻ āŠ†āŠĩāŦ€ āŠ…āŠĻāŦ‡ āŠ•āŦāŠĶāŠ°āŠĪāŦ€, āŠŪāŠūāŠĻāŠĩāŦ€āŠŊ āŠ…āŠĻāŦ‡ āŠŽāŦŒāŠ§āŦāŠ§āŠŋāŠ• āŠķāŠ•āŦāŠĪāŠŋ āŠđāŦ‹āŠĩāŠū āŠ›āŠĪāŠūāŠ‚ āŠ­āŠūāŠ°āŠĪāŠĶāŦ‡āŠķ āŠļāŠ‚āŠšāŠūāŠēāŠĻ āŠ•āŦāŠ·āŦ‡āŠĪāŦāŠ°āŦ‡ āŠ…āŠēāŦāŠŠāŠĩāŠŋāŠ•āŠļāŠŋāŠĪ āŠ°āŠđāŦāŠŊāŦ‹. āŠŠāŦāŠ°āŠļāŦāŠĪāŦāŠĪ āŠķāŦ‹āŠ§āŠĻāŠŋāŠŽāŠ‚āŠ§ āŠĶāŦāŠĩāŠūāŠ°āŠū āŠļāŠ‚āŠķāŦ‹āŠ§āŠ•āŠĻāŦ‹ āŠ‰āŠĶāŦ‡āŠķ āŠļāŦāŠĩāŠūāŠŪāŠŋāŠĻāŠūāŠ°āŠūāŠŊāŠĢ āŠļāŠ‚āŠŠāŦāŠ°āŠĶāŠūāŠŊāŠĻāŦ‹ āŠ‰āŠĶāŦāŠ­āŠĩ āŠ•āŦ‡āŠĩāŦ€ āŠ°āŦ€āŠĪāŦ‡ āŠĨāŠŊāŦ‹ āŠĪāŦ‡āŠŪāŠœ āŠķāŦāŠ°āŦ€āŠļāŠđāŠœāŠūāŠĻāŠ‚āŠĶāŠļāŦāŠĩāŠūāŠŪāŦ€āŠĻāŦāŠ‚ āŠœāŦ€āŠĩāŠĻ āŠ…āŠĻāŦ‡ āŠĪāŦ‡āŠŪāŠĻāŠū āŠĶāŦāŠĩāŠūāŠ°āŠū āŠ­āŠūāŠ°āŠĪāŠĻāŦ€ āŠŠāŠĩāŠŋāŠĪāŦāŠ°āŠ­āŦ‚āŠŪāŦ€ āŠŠāŠ° āŠĨāŠŊāŦ‡āŠē āŠŊāŦāŠ—āŠ•āŠūāŠ°āŦāŠŊāŠĻāŦ‡ āŠļāŠ‚āŠ•āŦāŠ·āŦ€āŠŠāŦāŠĪāŠŪāŠūāŠ‚ āŠļāŠŪāŠœāŠĩāŠūāŠĻāŦ‹ āŠ›āŦ‡. āŠĪāŦ‡āŠŪāŠĻāŦ€ āŠŪāŠūāŠĻāŦ‚āŠ·āŦ€āŠēāŦ€āŠēāŠū, āŠāŠķāŦāŠ°āŦāŠĩāŠ°āŦāŠŊ, āŠšāŠūāŠ°āŠŋāŠĪāŦāŠ°āŦāŠŊ, āŠĻāŦˆāŠĪāŠŋāŠ•āŠĪāŠū, āŠļāŠĶāŦāŠ—āŦāŠĢāŠŊāŦāŠ•āŦāŠĪ āŠ†āŠšāŠ°āŠĢāŠ­āŠ° āŠœāŦ€āŠĩāŠĻ āŠ…āŠĻāŦ‡ āŠ•āŠĩāŠĻāŠĻāŠū āŠĶāŠ°āŦ‡āŠ• āŠŠāŠūāŠļāŠūāŠĻāŦ€ āŠļāŦāŠ•āŦāŠ·āŦāŠŪāŠ›āŠĢāŠūāŠĩāŠŸ āŠ…āŠĻāŦ‡ āŠĪāŦ‡āŠŪāŠĢāŦ‡ āŠ†āŠŠāŦ‡āŠē āŠĪāŠĪāŦāŠĩāŠœāŦāŠžāŠūāŠĻ āŠļāŦāŠĩāŠūāŠŪāŠŋāŠĻāŠūāŠ°āŠūāŠŊāŠĢ āŠļāŠūāŠđāŠŋāŠĪāŦāŠŊāŠĻāŠū āŠ…āŠ­āŦāŠŊāŠūāŠļ āŠĶāŦāŠĩāŠūāŠ°āŠū āŠļāŠ‚āŠķāŦ‹āŠ§āŠ•āŦ‡ āŠ°āŠœāŦ‚ āŠ•āŠ°āŦ‡āŠē āŠ›āŦ‡

    Pregnancy with super-obesity: an emerging pandemic

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    Pregnancy associated with obesity is an upcoming challenge in high risk obstetrics management. Ironically, in India though half the population is under the malnutrition zone, it is known as the diabetic capital. This is attributed to the changing lifestyles which have led to a steep rise in medical disorders like hypertension, diabetes and obesity, especially in metropolitan cities. A case of pregnancy in a super obese woman with a successful outcome is presented here

    Nimotuzumab-cisplatin-radiation versus cisplatin-radiation in HPV negative oropharyngeal cancer

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    BACKGROUND: Addition of nimotuzumab to weekly cisplatin and radiation improves outcomes in head and neck cancer. HPV negative oropharyngeal cancer has unsatisfactory treatment outcomes and is a candidate for escalation of treatment. We wanted to determine whether the addition of nimotuzumab to cisplatin-radiation could improve outcomes in these poor-risk tumors.METHODS: This was a subgroup analysis of a phase 3 randomized study. In this study, locally advanced head and neck cancer patients undergoing definitive chemoradiation were randomly allocated to weekly cisplatin (30 mg/m2 IV)- radiation (66–70 Gy) {CRT arm} or nimotuzumab (200 mg weekly) -weekly cisplatin (30 mg/m2)-radiation (66–70 Gy) {NCRT arm}. The data of HPV negative oropharyngeal cancer was extracted from the database of this study for the analysis. HPV testing was done with p16 immunohistochemistry (IHC) staining and reported according to the CAP criteria. The outcomes assessed were progression-free survival (PFS), disease-free survival (DFS), locoregional control, and overall survival (OS). Interaction test was performed between the study arms and HPV status prior to doing any HPV specific analysis for each of the studied outcomes. Kaplan Meier estimates for 2 year OS with 95% CI was calculated. The hazard ratio was obtained using COX regression analysis.RESULTS: We had 187 HPV negative oropharyngeal cancers, 91 in the CRT arm and 96 in NCRT arm. The interaction test was significant for PFS (p = 0.000), locoregional control (p = 0.007) and overall survival (p = 0.002) but not for DFS (p = 0.072). The 2- year PFS was 31.5% (95%CI 21.5–42) in CRT arm versus 57.2% (95%CI 45.8–67.1) in NCRT arm (HR -0.54; 95%CI 0.36–0.79, p = 0.002). The 2-year LRC was 41.4% (95%CI 29.8–52.6) in the CRT arm versus in 60.4% (95%CI 48.7–70.2) in the NCRT arm (HR -0.61; 95%CI 0.4–0.94, p = 0.024). The addition of nimotuzumab also lead to an improvement in 2-year OS from 39.0% (95%CI 28.4–49.6) to 57.6% (95%CI 46.3–67.4) (HR-0.63, 95%CI 0.43–0.92, p = 0.018).CONCLUSIONS: The addition of nimotuzumab to weekly cisplatin-radiation improves outcomes inclusive of OS in HPV negative oropharyngeal cancers.<br/

    Nimotuzumab-cisplatin-radiation versus cisplatin-radiation in HPV negative oropharyngeal cancer

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    BACKGROUND: Addition of nimotuzumab to weekly cisplatin and radiation improves outcomes in head and neck cancer. HPV negative oropharyngeal cancer has unsatisfactory treatment outcomes and is a candidate for escalation of treatment. We wanted to determine whether the addition of nimotuzumab to cisplatin-radiation could improve outcomes in these poor-risk tumors.METHODS: This was a subgroup analysis of a phase 3 randomized study. In this study, locally advanced head and neck cancer patients undergoing definitive chemoradiation were randomly allocated to weekly cisplatin (30 mg/m2 IV)- radiation (66–70 Gy) {CRT arm} or nimotuzumab (200 mg weekly) -weekly cisplatin (30 mg/m2)-radiation (66–70 Gy) {NCRT arm}. The data of HPV negative oropharyngeal cancer was extracted from the database of this study for the analysis. HPV testing was done with p16 immunohistochemistry (IHC) staining and reported according to the CAP criteria. The outcomes assessed were progression-free survival (PFS), disease-free survival (DFS), locoregional control, and overall survival (OS). Interaction test was performed between the study arms and HPV status prior to doing any HPV specific analysis for each of the studied outcomes. Kaplan Meier estimates for 2 year OS with 95% CI was calculated. The hazard ratio was obtained using COX regression analysis.RESULTS: We had 187 HPV negative oropharyngeal cancers, 91 in the CRT arm and 96 in NCRT arm. The interaction test was significant for PFS (p = 0.000), locoregional control (p = 0.007) and overall survival (p = 0.002) but not for DFS (p = 0.072). The 2- year PFS was 31.5% (95%CI 21.5–42) in CRT arm versus 57.2% (95%CI 45.8–67.1) in NCRT arm (HR -0.54; 95%CI 0.36–0.79, p = 0.002). The 2-year LRC was 41.4% (95%CI 29.8–52.6) in the CRT arm versus in 60.4% (95%CI 48.7–70.2) in the NCRT arm (HR -0.61; 95%CI 0.4–0.94, p = 0.024). The addition of nimotuzumab also lead to an improvement in 2-year OS from 39.0% (95%CI 28.4–49.6) to 57.6% (95%CI 46.3–67.4) (HR-0.63, 95%CI 0.43–0.92, p = 0.018).CONCLUSIONS: The addition of nimotuzumab to weekly cisplatin-radiation improves outcomes inclusive of OS in HPV negative oropharyngeal cancers.<br/

    Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction

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    The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N=293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease. On the electrocardiogram, the PR interval reflects conduction from the atria to ventricles and also serves as risk indicator of cardiovascular morbidity and mortality. Here, the authors perform genome-wide meta-analyses for PR interval in multiple ancestries and identify 141 previously unreported genetic loci.Peer reviewe

    ÐĪÐūŅ€ÐžÐļŅ€ÐūÐēÐ°Ð―ÐļÐĩ ŅÐžÐūŅ†ÐļÐūÐ―Ð°ÐŧŅŒÐ―ÐūÐđ КŅƒÐŧŅŒŅ‚ŅƒŅ€Ņ‹ КаК КÐūОÐŋÐūÐ―ÐĩÐ―Ņ‚а ÐļÐ―Ð―ÐūÐēаŅ†ÐļÐūÐ―Ð―ÐūÐđ КŅƒÐŧŅŒŅ‚ŅƒŅ€Ņ‹ ŅŅ‚ŅƒÐīÐĩÐ―Ņ‚ÐūÐē

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    Homozygosity has long been associated with rare, often devastating, Mendelian disorders1 and Darwin was one of the first to recognise that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity, ROH), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use ROH to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts and find statistically significant associations between summed runs of homozygosity (SROH) and four complex traits: height, forced expiratory lung volume in 1 second (FEV1), general cognitive ability (g) and educational attainment (nominal p<1 × 10−300, 2.1 × 10−6, 2.5 × 10−10, 1.8 × 10−10). In each case increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing convincing evidence for the first time that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been

    Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

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    We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

    Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

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    Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

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    Publisher Copyright: ÂĐ 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

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    Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska LÃĪkaresÃĪllskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD
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