Akhil Pampana Pampana

Dr. Akhil Pampana Pampana

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 August 2020 in Nature Genetics
Verified
Journal Article
Closed access
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Xihao LiXihao Li
Xihao Li
Zilin LiZilin Li
Zilin Li
HZHufeng Zhou
Hufeng Zhou
SGSheila M. Gaynor
Sheila M. Gaynor
YLYaowu Liu
Yaowu Liu
XLXihong Lin
Xihong Lin

19 August 2022 in Science Advances
Verified
Journal Article
Open access
DKDaniel H. Katz
Daniel H. Katz
JRJeremy M. Robbins
Jeremy M. Robbins
SDShuliang Deng
Shuliang Deng
UTUsman A. Tahir
Usman A. Tahir
ABAlexander G. Bick
Alexander G. Bick
RGRobert E. Gerszten
Robert E. Gerszten
High-throughput proteomic profiling using antibody or aptamer-based affinity reagents is used increasingly in human studies. However, direct analyses to address the relative strengths and weaknesses of these platforms are lacking. We assessed findings from the SomaScan1.3K ( N = 1301 reagents), the SomaScan5K platform ( N = 4979 reagents), and the Olink Explore ( N = 1472 reagents) profiling techniques in 568 adults from the Jackson Heart Study and 219 participants in the HERITAGE Family Study across four performance domains: precision, accuracy, analytic breadth, and phenotypic associations leveraging detailed clinical phenotyping and genetic data. Across these studies, we show evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the Olink platform, while the Soma platforms benefit from greater measurement precision and analytic breadth across the proteome.

7 June 2021 in Nature Medicine
Verified
Journal Article
Closed access
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SZSeyedeh M. Zekavat
Seyedeh M. Zekavat
SLShu-Hong Lin
Shu-Hong Lin
ABAlexander G. Bick
Alexander G. Bick
ALAoxing Liu
Aoxing Liu
KPKaavya Paruchuri
Kaavya Paruchuri
PNPradeep Natarajan
Pradeep Natarajan

11 January 2022 in Circulation
Verified
Journal Article
Open access
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SZSeyedeh Maryam Zekavat
Seyedeh Maryam Zekavat
VRVineet K. Raghu
Vineet K. Raghu
MTMark Trinder
Mark Trinder
YYYixuan Ye
Yixuan Ye
SKSatoshi Koyama
Satoshi Koyama
PNPradeep Natarajan
Pradeep Natarajan
Background: The microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health and tumorigenesis. The retinal fundus is a window for human in vivo noninvasive assessment of the microvasculature. Large-scale complementary machine learning-based assessment of the retinal vasculature with phenome-wide and genome-wide analyses may yield new insights into human health and disease. Methods: We used 97 895 retinal fundus images from 54 813 UK Biobank participants. Using convolutional neural networks to segment the retinal microvasculature, we calculated vascular density and fractal dimension as a measure of vascular branching complexity. We associated these indices with 1866 incident International Classification of Diseases –based conditions (median 10-year follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity. Results: Low retinal vascular fractal dimension and density were significantly associated with higher risks for incident mortality, hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions, as well as corresponding quantitative traits. Genome-wide association of vascular fractal dimension and density identified 7 and 13 novel loci, respectively, that were enriched for pathways linked to angiogenesis (eg, vascular endothelial growth factor, platelet-derived growth factor receptor, angiopoietin, and WNT signaling pathways) and inflammation (eg, interleukin, cytokine signaling). Conclusions: Our results indicate that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease and provide insights into genes and biological pathways influencing microvascular indices. Moreover, such a framework highlights how deep learning of images can quantify an interpretable phenotype for integration with electronic health record, biomarker, and genetic data to inform risk prediction and risk modification.

12 September 2022 in Nature Communications
Verified
Journal Article
Open access
PDF file
MUM D Mesbah Uddin
M D Mesbah Uddin
NNNgoc Quynh H. Nguyen
Ngoc Quynh H. Nguyen
BYBing Yu
Bing Yu
JBJennifer A. Brody
Jennifer A. Brody
APAkhil Pampana Pampana
Akhil Pampana Pampana
KCKaren N. Conneely
Karen N. Conneely
Age-related changes to the genome-wide DNA methylation (DNAm) pattern observed in blood are well-documented. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by the age-related acquisition and expansion of leukemogenic mutations in hematopoietic stem cells (HSCs), is associated with blood cancer and coronary artery disease (CAD). Epigenetic regulators DNMT3A and TET2 are the two most frequently mutated CHIP genes. Here, we present results from an epigenome-wide association study for CHIP in 582 Cardiovascular Health Study (CHS) participants, with replication in 2655 Atherosclerosis Risk in Communities (ARIC) Study participants. We show that DNMT3A and TET2 CHIP have distinct and directionally opposing genome-wide DNAm association patterns consistent with their regulatory roles, albeit both promoting self-renewal of HSCs. Mendelian randomization analyses indicate that a subset of DNAm alterations associated with these two leading CHIP genes may promote the risk for CAD.

8 April 2022 in Science Advances
Verified
Journal Article
Closed access
TNTetsushi Nakao
Tetsushi Nakao
ABAlexander G Bick
Alexander G Bick
MTMargaret A Taub
Margaret A Taub
SZSeyedeh M Zekavat
Seyedeh M Zekavat
MUM Uddin
M Uddin
PNPradeep Natarajan
Pradeep Natarajan
Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program ( n = 63,302) and UK Biobank ( n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.