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MSTPublications: May 2024

Posted by on Thursday, May 30, 2024 in New Publications .

Phenomewide Association Study of Health Outcomes Associated With the Genetic Correlates of 25 Hydroxyvitamin D Concentration and Vitamin D Binding Protein Concentration.
Kresge HA, Blostein F, Goleva S, Albiñana C, Revez JA, Wray NR, Vilhjálmsson BJ, Zhu Z, McGrath JJ, Davis LK.
Twin Res Hum Genet. 2024 Apr 22:1-11. doi: 10.1017/thg.2024.19. Online ahead of print.

While it is known that vitamin D deficiency is associated with adverse bone outcomes, it remains unclear whether low vitamin D status may increase the risk of a wider range of health outcomes. We had the opportunity to explore the association between common genetic variants associated with both 25 hydroxyvitamin D (25OHD) and the vitamin D binding protein (DBP, encoded by the GC gene) with a comprehensive range of health disorders and laboratory tests in a large academic medical center. We used summary statistics for 25OHD and DBP to generate polygenic scores (PGS) for 66,482 participants with primarily European ancestry and 13,285 participants with primarily African ancestry from the Vanderbilt University Medical Center Biobank (BioVU). We examined the predictive properties of PGS25OHD, and two scores related to DBP concentration with respect to 1322 health-related phenotypes and 315 laboratory-measured phenotypes from electronic health records. In those with European ancestry: (a) the PGS25OHD and PGSDBP scores, and individual SNPs rs4588 and rs7041 were associated with both 25OHD concentration and 1,25 dihydroxyvitamin D concentrations; (b) higher PGS25OHD was associated with decreased concentrations of triglycerides and cholesterol, and reduced risks of vitamin D deficiency, disorders of lipid metabolism, and diabetes. In general, the findings for the African ancestry group were consistent with findings from the European ancestry analyses. Our study confirms the utility of PGS and two key variants within the GC gene (rs4588 and rs7041) to predict the risk of vitamin D deficiency in clinical settings and highlights the shared biology between vitamin D-related genetic pathways a range of health outcomes.

 

Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures From Routine EHRs for Pulmonary Nodule Classification.
Li TZ, Still JM, Xu K, Lee HH, Cai LY, Krishnan AR, Gao R, Khan MS, Antic S, Kammer M, Sandler KL, Maldonado F, Landman BA, Lasko TA.
Med Image Comput Comput Assist Interv. 2023 Oct;14221:649-659. doi: 10.1007/978-3-031-43895-0_61. Epub 2023 Oct 1.

The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by incorporating repeat imaging and medical context, such as electronic health records (EHRs). However, clinically routine modalities such as imaging and diagnostic codes can be asynchronous and irregularly sampled over different time scales which are obstacles to longitudinal multimodal learning. In this work, we propose a transformer-based multimodal strategy to integrate repeat imaging with longitudinal clinical signatures from routinely collected EHRs for SPN classification. We perform unsupervised disentanglement of latent clinical signatures and leverage time-distance scaled self-attention to jointly learn from clinical signatures expressions and chest computed tomography (CT) scans. Our classifier is pretrained on 2,668 scans from a public dataset and 1,149 subjects with longitudinal chest CTs, billing codes, medications, and laboratory tests from EHRs of our home institution. Evaluation on 227 subjects with challenging SPNs revealed a significant AUC improvement over a longitudinal multimodal baseline (0.824 vs 0.752 AUC), as well as improvements over a single cross-section multimodal scenario (0.809 AUC) and a longitudinal imaging-only scenario (0.741 AUC). This work demonstrates significant advantages with a novel approach for co-learning longitudinal imaging and non-imaging phenotypes with transformers. Code available at https://github.com/MASILab/lmsignatures.

 

Determinants of mosaic chromosomal alteration fitness.
Pershad Y, Mack T, Poisner H, Jakubek YA, Stilp AM, Mitchell BD, Lewis JP, Boerwinkle E, Loos RJF, Chami N, Wang Z, Barnes K, Pankratz N, Fornage M, Redline S, Psaty BM, Bis JC, Shojaie A, Silverman EK, Cho MH, Yun JH, DeMeo D, Levy D, Johnson AD, Mathias RA, Taub MA, Arnett D, North KE, Raffield LM, Carson AP, Doyle MF, Rich SS, Rotter JI, Guo X, Cox NJ, Roden DM, Franceschini N, Desai P, Reiner AP, Auer PL, Scheet PA, Jaiswal S, Weinstock JS, Bick AG.
Nat Commun. 2024 May 7;15(1):3800. doi: 10.1038/s41467-024-48190-8.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.

 

The E592K variant of SF3B1 creates unique RNA missplicing and associates with high-risk MDS without ring sideroblasts.
Choi IY, Ling JP, Zhang J, Helmenstine E, Walter W, Tsakiroglou P, Bergman RE, Philippe C, Manley JL, Rouault-Pierre K, Li B, Wiseman DH, Batta K, Ouseph MM, Bernard E, Dubner B, Li X, Haferlach T, Koget A, Fazal S, Jain T, Gocke CD, DeZern AE, Dalton WB.
Blood Adv. 2024 May 17:bloodadvances.2023011260. doi: 10.1182/bloodadvances.2023011260. Online ahead of print.

Empirical assessment of the assumptions of ComBat with diffusion tensor imaging.
Kim ME, Gao C, Cai LY, Yang Q, Newlin NR, Ramadass K, Jefferson A, Archer D, Shashikumar N, Pechman KR, Gifford KA, Hohman TJ, Beason-Held LL, Resnick SM, Winzeck S, Schilling KG, Zhang P, Moyer D, Landman BA.
J Med Imaging (Bellingham). 2024 Mar;11(2):024011. doi: 10.1117/1.JMI.11.2.024011. Epub 2024 Apr 17.

Individualized Dose-Response to Statins Associated with Cardiovascular Disease Outcomes.
Aggarwal SK, Jiang L, Liu G, Grabowska ME, Ong HH, Wilke RA, Feng Q, Wei WQ.
JACC Adv. 2024 Apr;3(4):100894. doi: 10.1016/j.jacadv.2024.100894. Epub 2024 Mar 7.

Belief Updating, Childhood Maltreatment, and Paranoia in Schizophrenia-Spectrum Disorders.
Sloan AF, Kittleson AR, Torregrossa LJ, Feola B, Rossi-Goldthorpe R, Corlett PR, Sheffield JM. 2024 May 3:sbae057. doi: 10.1093/schbul/sbae057. Epub ahead of print.

The Lung Cancer Prediction Model “Stress Test”: Assessment of Models’ Performance in a High-Risk Prospective Pulmonary Nodule Cohort.
Heideman BE, Kammer MN, Paez R, Swanson T, Godfrey CM, Low SW, Xiao D, Li TZ, Richardson JR, Knight MA, Shojaee S, Deppen SA, Lentz RJ, Grogan EL, Maldonado F.
CHEST Pulm. 2024 Mar;2(1):100033. doi: 10.1016/j.chpulm.2023.100033. Epub 2023 Dec 26.

Resident Salary Compared to Living Wages at United States Training Institutions.
Liles C, Tang AR, Petrovic M, Dambrino RJ 4th, Thompson RC, Chambless LB.
Ann Surg. 2024 May 10. doi: 10.1097/SLA.0000000000006335. Online ahead of print.

Clinical associations with a polygenic predisposition to benign lower white blood cell counts.
Mosley JD, Shelley JP, Dickson AL, Zanussi J, Daniel LL, Zheng NS, Bastarache L, Wei WQ, Shi M, Jarvik GP, Rosenthal EA, Khan A, Sherafati A, Kullo IJ, Walunas TL, Glessner J, Hakonarson H, Cox NJ, Roden DM, Frangakis SG, Vanderwerff B, Stein CM, Van Driest SL, Borinstein SC, Shu XO, Zawistowski M, Chung CP, Kawai VK.
Nat Commun. 2024 Apr 22;15(1):3384. doi: 10.1038/s41467-024-47804-5.

Kidney collecting-duct-derived vasopressin is not essential for appropriate concentration or dilution of urine.
Zuchowski Y, Carty J, Trapani JB, Watts J, Bock F, Zhang M, Terker A, Zent R, Delpire E, Harris RC, Arroyo JP.
Am J Physiol Renal Physiol. 2024 May 2. doi: 10.1152/ajprenal.00057.2024. Online ahead of print.

Sensorimotor regulation of facial expression – An untouched frontier.
Bress KS, Cascio CJ.
Neurosci Biobehav Rev. 2024 May 6;162:105684. doi: 10.1016/j.neubiorev.2024.105684. Online ahead of print. Review.