Biology subjects

Knight, E.

Publications and source records attributed to Knight, E..

5 recordsLinked to original sources

bioRxiv2024

Homomorphic Encryption: An Application to Polygenic Risk Scores

1BackgroundPolygenic risk scores (PRSs) have emerged as a powerful tool in precision medicine, enabling personalized risk assessments for complex diseases. However, the use of sensitive genomic data in PRS calculations raises concerns about privacy and security. Fully homomorphic encryption (FHE) offers a promising solution by allowing computations on encrypted data, preserving the privacy of both genomic information and PRS models. MethodsHere, we present an application of FHE for encrypted PRS calculations using a particular protocol (CKKS) within the Lattigo library. Our approach involves a three-party system: clients (clinicians handling sensitive genetic data), modelers developing a PRS (academics or companies), and evaluators (a local hospital running the models while maintaining data confidentiality). We demonstrate the feasibility and accuracy of our approach by applying it to synthetic datasets of various sizes and to a robust 110k-single-nucleotide polymorphism (SNP) model for schizophrenia. The complete codebase and a sample dataset are available at https://github.com/gersteinlab/HEPRS. ResultsThe difference between traditional plaintext and encrypted PRS calculation results is negligible: the R2 is 0.999 and the mean squared error is 2.27 x 10-6. Moreover, while the encrypted calculation is roughly 1,000 times slower than conventional non-encrypted ones (when considering only the core PRS calculation), the computation remains feasible on a single-CPU node. For example, processing [~]1,100 individuals with [~]110k SNPs took six minutes and [~]65 GB of memory on a laptop computer. In addition, we investigated the impact of the encryption parameters on the computational time and accuracy in detail, showing the expected slowdown with higher security settings. ConclusionOur approach showcases the applicability and feasibility of using FHE on real-world PRS models. With the pressing need for privacy-preserving solutions in the era of precision medicine, our work serves as a pilot application, offering a simple use case and providing a detailed comparison and evaluation in terms of accuracy, cost, and scalability.

bioinformatics↗

bioRxiv2023

Protein language model-guided engineering of an anti-CRISPR protein for precise genome editing in human cells

Promiscuous editing by CRISPR/Cas systems within the human genome is a major challenge that must be addressed prior to applying these systems therapeutically. In bacteria, CRISPR/Cas systems have evolved in a co-evolutionary arms race with infectious phage viruses that contain inhibitory anti-CRISPR proteins within their genomes. Here, we harness the outcome of this co-evolutionary arms race to engineer an AcrIIA4 anti-CRISPR protein to increase the precision of CRISPR/Cas-based genome targeting. We developed an approach that specifically leveraged (1) protein language models, (2) deep mutational scanning, and (3) highly parallel DNA repair measurements within human cells. In a single experiment, [~]10,000 AcrIIA4 variants were tested to identify lead AcrIIA4 variants that eliminated detectable off-target editing events while retaining on-target activity. The candidates were further tested in a focused round of screening that included a high-fidelity version of Cas9 as a benchmark. Finally, arrayed experiments using Cas9 delivered as ribonucleoprotein were conducted that demonstrated an increase in gene editing precision across two independent genomic loci and a reduction in the frequency of translocation events between an on-target and off-target site. Thus, language-model-guided high-throughput screening is an effective way to efficiently engineer AcrIIA4 to increase gene editing precision, which could be used to improve the fidelity of gene editing-based therapeutics and to reduce genotoxicity.

synthetic biology↗

bioRxiv2023

Assessing an age-old ecogeographical rule in nightjars across the full annual cycle

Bergmanns rule states that homeotherms are larger in colder climates (which occur at higher latitudes and elevations) due to thermoregulatory mechanisms. Despite being perhaps the most extensively studied biogeographical rule across all organisms, consistent mechanisms explaining which species or taxa adhere to Bergmanns rule have been elusive. Furthermore, evidence for Bergmanns rule in migratory animals has been mixed, and it was difficult to assess how environmental conditions across the full annual cycle impact body size until the recent miniaturization of tracking technology. Nightjars (Family Caprimulgidae), nocturnal birds with physiological and behavioral adaptations (e.g., torpor) to cope with the environmental extremes they often experience, offer a unique opportunity to elucidate the mechanisms underpinning Bergmanns rule. Many nightjar species are strongly migratory and have large breeding ranges, offering the opportunity to look at variation in potential drivers within and across seasons of the annual cycle. Furthermore, variation in migration strategy within the family provides an opportunity to separate adaptations for migration strategy from adaptations for thermal tolerance. In this study, we use cross-continental data from three species of nightjars (Common nighthawk, Eastern whip-poor-will, and European nightjar) to assess 1) whether migratory species in this clade adheres to Bergmanns rule, 2) which environmental factors are the best predictors of body size, and 3) the extent to which environmental conditions across the full annual cycle determine body size. For each species, we use breeding and winter location data from GPS tags to compare competing hypotheses explaining variation in body size: temperature regulation, productivity, and seasonality (during both the breeding and wintering periods), and migration distance. We found that Common nighthawk and Eastern whip-poor-will exhibit Bergmannian patterns in body size while European nightjar does not, although the spread of tag deployment sites on the breeding grounds was minimal for the European nightjar. Predictor variables associated with nightjar breeding locations more often explained body size than did variables on the wintering grounds. Surprisingly, models representing the geography hypothesis were best represented among important models in our final data set. Latitude and longitude correlated strongly with environmental variables and migratory distance; thus, these geographical variables offer a composite variable of sorts, summarizing many factors that likely influence body size in nightjars. Leveraging multi-species and cross-continental data across the full annual cycle, along with global environmental data, can provide insight into long-standing questions and will be important for understanding the generalizability of Bergmanns rule.

zoology↗

bioRxiv2023

Resting EEG Periodic and Aperiodic Components Predict Cognitive Decline Over 10 Years

Measures of intrinsic brain function at rest show promise as predictors of cognitive decline in humans, including EEG metrics such as individual alpha peak frequency (IAPF) and the aperiodic exponent, reflecting the strongest frequency of alpha oscillations and the relative balance of excitatory:inhibitory neural activity, respectively. Both IAPF and the aperiodic exponent decrease with age and have been associated with worse executive function and working memory. However, few studies have jointly examined their associations with cognitive function, and none have examined their association with longitudinal cognitive decline rather than cross-sectional impairment. In a preregistered secondary analysis of data from the longitudinal Midlife in the United States (MIDUS) study, we tested whether IAPF and aperiodic exponent measured at rest predict cognitive function (N = 235; age at EEG recording M = 55.10, SD = 10.71) over 10 years. The IAPF and the aperiodic exponent interacted to predict decline in overall cognitive ability, even after controlling for age, sex, education, and lag between data collection timepoints. Post-hoc tests showed that "mismatched" IAPF and aperiodic exponents (e.g., higher exponent with lower IAPF) predicted greater cognitive decline compared to "matching" IAPF and aperiodic exponents (e.g., higher exponent with higher IAPF; lower IAPF with lower aperiodic exponent). These effects were largely driven by measures of executive function. Our findings provide the first evidence that IAPF and the aperiodic exponent are joint predictors of cognitive decline from midlife into old age and thus may offer a useful clinical tool for predicting cognitive risk in aging. Significance StatementMeasures of intrinsic brain function at rest assessed noninvasively from the scalp using electroencephalography (EEG) show promise as predictors of cognitive decline in humans. Using data from 235 participants from the Midlife in the United States (MIDUS) longitudinal study, we found two resting EEG markers (individual peak alpha frequency and aperiodic exponent) interacted to predict cognitive decline over a span of 10 years. Follow-up analyses revealed that "mismatched" markers (i.e., high in one and low in the other) predicted greater cognitive decline compared to "matching" markers. Because of the low cost and ease of collecting EEG data at rest, the current research provides evidence for possible scalable clinical applications for identifying individuals at risk for accelerated cognitive decline.

neuroscience↗

bioRxiv2022

mRNA decapping machinery targets LBD3/ASL9 transcripts to allow developmental changes in Arabidopsis

Multicellular organisms perceive and transduce multiple cues to optimize development. Key transcription factors drive developmental changes, but RNA processing also contributes to tissue development. Here, we report that multiple decapping deficient mutants share developmental defects in apical hook, primary and lateral root growth. More specifically, LATERAL ORGAN BOUNDARIES DOMAIN 3 (LBD3)/ASYMMETRIC LEAVES 2-LIKE 9 (ASL9) transcripts accumulate in decapping deficient plants and can be found in complexes with decapping components. Accumulation of ASL9 inhibits apical hook, primary root growth and lateral root formation. Interestingly, exogenous auxin application restores lateral roots formation in both ASL9 over-expressors and mRNA decay-deficient mutants. Likewise, mutations in the cytokinin transcription factors type-B ARABIDOPSIS RESPONSE REGULATORS (B-ARRs) ARR10 and ARR12 restore the developmental defects caused by over-accumulation of capped ASL9 transcript upon ASL9 overexpression. Most importantly, loss-of-function of asl9 partially restores apical hook and lateral root formation in decapping deficient mutants. Thus, the mRNA decay machinery directly targets ASL9 transcripts for decay, possibly to interfere with cytokinin/auxin responses, during development.

developmental biology↗