From d19acc86e3ce528b0e1512fda91c5ac04c854afd Mon Sep 17 00:00:00 2001 From: Anish Shah Date: Tue, 30 Apr 2024 22:03:03 -0500 Subject: [PATCH] update site --- grants/aha-innovative-project-loi-2024.docx | Bin 15365 -> 15386 bytes grants/aha-innovative-project-loi-2024.html | 235 +- grants/aha_innovative_project_2022.docx | Bin 14981 -> 15003 bytes site_libs/bootstrap/bootstrap.min.css | 4 +- t32/afgen-fellowship.html | 795 ++++++ t32/idp.docx | Bin 21151 -> 21186 bytes t32/phenotype-af.html | 273 +- t32/rip.html | 106 +- t32/tpipcvm-rip-seminar-021223.html | 2027 +++++++-------- .../figure-revealjs/fig-dag-1.png | Bin 213800 -> 211865 bytes t32/tpipcvm-rip-seminar-121823.html | 2306 ++++++++--------- .../figure-revealjs/fig-coumel-simple-1.png | Bin 127571 -> 121868 bytes 12 files changed, 3286 insertions(+), 2460 deletions(-) create mode 100644 t32/afgen-fellowship.html diff --git a/grants/aha-innovative-project-loi-2024.docx b/grants/aha-innovative-project-loi-2024.docx index ed0261463c29eb8ec093b49b08c30499ed54bdc5..309dfa8b43c1ef215aaf040e713ed15d04e8fb29 100644 GIT binary patch delta 1196 zcmZpzm{lPi;LXe;!obAA!QfvpFM=au*STg!28LdC1_t5Dd=_H$Tc@7(J8U4}TCaLa zOf@f3q2*TuL#&hPDfS)Tmh^VmPP2Xa`29>36DN*I)3(j_ICo}Fb#1ct;+N+{F0$2} zxY+kN(W*mv16OHY_~Re7hTiWUzf9S3!n`scI~H6^Nb$JX_|&WIp2wr5 z@to>c+hZDc$nv~vaq>>kTv*>F=0P<$9p~#it+V+!uejXIl$w#clc{%=iOr-(M%v8f&GQVG zT&sL~q;{R+EN_4PO9sI?7qd6EK9v?I{H6HTZ)yB?CaZofr-XT$m-0W99j~|ASidx~ z>G{3WzcViW)jM?c5Qn?EW6imRm3-&F1t$M8H4ck7k;*vzent1Yl7pX%`}H`&tZy@i zT=#7DyV1eyZ&`BuUYGWl{~iwtj<0@sS@pC-#<_b%&6Z(%EnjcZe;}p4_u04C+grM= zGql~FZM)y$6kHmw*v0&F26sow#C0ESqe@UF{iHf-ENx!L$iv72im%Q4m={9Vdraf%W6&JM4SZXG{^Goq2*DrG}X>3n$(V28u zt?+G=;EYon7RH^JdxK%E#O~#60UC|&Jp=XX452`O^=_5K1cgQ{jp!hxhEsezZe z#T92%Y)%aLXVH7CxqbGv%@#Yq2l^k|_r80d+#1b#Py6_J_uB%CbCtQY8@KdMk})m2 zVD@E`kG7=40`AA(LYCaVb8um~Fy3Cihsl z?Xr?${4@Egl><|m=HyyUaRGGKPOh_-VyZTnJj>daNy=n$y_wi#J!>tUS*8pO<@rS^ j`f2%jB_WAPIjMRTxj6yetZX0)1%Qx;g@NIRIfw@Ug~j1n delta 1283 zcmbPL(OOX-;LXe;!obAA!O*a{H+=E$^Y`)@85mUA85o2a7#O0R^Ycnl^Gf1FDhpDJ zWA!R>bGC+_%xg9f_$&G(o7Jys#VRe8cD>_fL6`Xp&N!@ji}lmjFh$jVoEkl=`0DM*`p!JpS>T#n*z^8kV7Xq!=liqk8BwEX^C3naMix+HZN9{`kQ2fx=dpr_ zP2S481R@m6w}KVI;uP7(2VtF7a)N3VRAFJ{1R0{5q%9K- zmPw2(y9{#AyY4z`E5j}x;&aNkbY8}%rc*&ec2DQmSY>3smejG; ztm$uFmz?qaFPd>_a^6?_4)Ft1eta|EvVU`!+6HL2acNX@Y+hm-#>9i1Z8mor2(yYa zGBGe<$x4$2EleUnLA||v$@}NPOmzvUjvGiLzyd}FhWMh?oML@F5E{w>ODV?5lhrJB - + -Research – aha-innovative-project-loi-2024 +Research + + + + + + + + + +
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Atrial Fibrillation Genetics Fellowship

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+Anish S. Shah, MD, MS +
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+ University of Illinois at Chicago +

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+ Emory University +

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About Me

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I am a 4th year general CV fellow on the research track (T32/F32) at UIC (2 + 2), pursuing additional fellowship in clinical EP, with a near-term goal of applying for K23 award. My overall interest is in phenotying paroxysmal AF to better understand underlying autonomic contributions.

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  • Extensive programming background (primarily in R, Python, and MATLAB), DSP for surface and intracrdiac electrograms, epidemiology/biostatistics (trained @ RSPH)
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  • Interest in computational genetics (PLINK, Merlin, BioConductor) for novel rare variant identification
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  • Plan to join academic EP position, with long-term goal of better understanding how to individualize and target AF therapies (e.g. cardioneural ablation, trigger-focused, dispersion-based mapping, pharmacological)
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Project Overview

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Deleterious mutations in sarcomeric proteins, such as TTN, have an association with atrial fibrillation (Yoneda et al. 2021), but there are a broad number of VUS that have unknown impact. Genetic variants also manifest at the level of surface ECG, but have not been studied in VUS (Verweij et al. 2020).

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Hypothesis: Using the TTN gene as a case study, ECG features can be extracted that classify and identify samples with deleterious variants, based on in silico predictors (PolyPhen, SIFT, REVEL), in a population with AF.

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Proposal:

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  1. Use computational genetics approach to quantify potential deleterious TTN variants in a training sample of n = 300 WES samples with AF.
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  3. Use single-beat, sinus ECG features (approximately beats = 40,000) to train a classification model using a deep neural network approach.
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  5. Test model in an additional, prospectively enrolled cohort of n = 240 with WES over upcoming 3 months.
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  7. Validate model in external data through AFGen collaborations.
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References

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+Verweij, Niek, Jan-Walter Benjamins, Michael P. Morley, Yordi J. Van De Vegte, Alexander Teumer, Teresa Trenkwalder, Wibke Reinhard, Thomas P. Cappola, and Pim Van Der Harst. 2020. “The Genetic Makeup of the Electrocardiogram.” Cell Systems 11 (3): 229–238.e5. https://doi.org/10.1016/j.cels.2020.08.005. +
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+Yoneda, Zachary T., Katherine C. Anderson, Joseph A. Quintana, Matthew J. O’Neill, Richard A. Sims, Andrew M. Glazer, Christian M. Shaffer, et al. 2021. “Early-Onset Atrial Fibrillation and the Prevalence of Rare Variants in Cardiomyopathy and Arrhythmia Genes.” JAMA Cardiology 6 (12): 1371–79. https://doi.org/10.1001/jamacardio.2021.3370. +
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