Biology subjects

Wheeler, M. T.

Publications and source records attributed to Wheeler, M. T..

14 recordsLinked to original sources

bioRxiv2026

Multi-Omic, Multi-Tissue Responses to Acute Exercise in Sedentary Adults: Findings from the Molecular Transducers of Physical Activity Consortium

Regular physical activity represents one of the greatest mechanisms for maintaining human health, yet the underlying molecular transducers of these benefits remain incompletely understood. Multi-omic assays now provide new opportunities to study the coordinated molecular responses of body tissues to different exercise modalities. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to address this need by creating a molecular map of the response to physical activity. Described here is the first human cohort of MoTrPAC: sedentary adults enrolled prior to study suspension during the COVID-19 pandemic (N=175) randomized to either endurance or resistance exercise, or non-exercise control. From these participants, we detail their global acute molecular response in skeletal muscle, adipose tissue, and blood, integrated at multiple levels: tissue, exercise modality, timepoint, and omic category. These analyses characterize key molecular pathways, identify central regulators, and implicate novel candidate exerkines in mediating multi-organ exercise effects.

systems biology↗

bioRxiv2025

Biomni: A General-Purpose Biomedical AI Agent

Biomedical research underpins progress in our understanding of human health and disease, drug discovery, and clinical care. However, with the growth of complex lab experiments, large datasets, many analytical tools, and expansive literature, biomedical research is increasingly constrained by repetitive and fragmented workflows that slow discovery and limit innovation, underscoring the need for a fundamentally new way to scale scientific expertise. Here, we introduce Biomni, a general-purpose biomedical AI agent designed to autonomously execute a wide spectrum of research tasks across diverse biomedical subfields. To systematically map the biomedical action space, Biomni first employs an action discovery agent to create the first unified agentic environment - mining essential tools, databases, and protocols from tens of thousands of publications across 25 biomedical domains. Built on this foundation, Biomni features a generalist agentic architecture that integrates large language model (LLM) reasoning with retrieval-augmented planning and code-based execution, enabling it to dynamically compose and carry out complex biomedical workflows - entirely without relying on predefined templates or rigid task flows. Systematic benchmarking demonstrates that Biomni achieves strong generalization across heterogeneous biomedical tasks - including causal gene prioritization, drug repurposing, rare disease diagnosis, micro-biome analysis, and molecular cloning - without any task-specific prompt tuning. Real-world case studies further showcase Biomnis ability to interpret complex, multi-modal biomedical datasets and autonomously generate experimentally testable protocols. Biomni envisions a future where virtual AI biologists operate alongside and augment human scientists to dramatically enhance research productivity, clinical insight, and healthcare. Biomni is ready to use at https://biomni.stanford.edu, and we invite scientists to explore its capabilities, stress-test its limits, and co-create the next era of biomedical discoveries.

bioinformatics↗

bioRxiv2025

Scaled multidimensional assays of variant effect identify sequence-function relationships in hypertrophic cardiomyopathy

BackgroundAn estimated 1 in 500 people live with hypertrophic cardiomyopathy (HCM), a disease for which genetic diagnosis can identify family members at risk, and increasingly guide therapy. Mutations in the myosin binding protein C3 (MYBPC3) gene account for a significant proportion of HCM cases. However, many of these variants are classified as variants of uncertain significance (VUS), complicating clinical decision-making. Scalable methods for variant interpretation in disease-specific cell types are crucial for understanding variant impact and uncovering disease mechanisms. MethodsWe developed a scaled multidimensional mapping strategy to evaluate the functional impact of variants across a critical domain of MYBPC3. We incorporate saturation base editing at the native MYBPC3 locus, a long-read RNA sequencing-enabled assay of variant splice effects, and measurements of HCM-relevant phenotypes, including MYBPC3 abundance, hypertrophic signaling, and ubiquitin-proteasome function in human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). ResultsOur multidimensional mapping strategy enabled high-resolution functional analysis of MYBPC3 variants in iPSC-CMs. Targeted transient base editing generated a comprehensive variant library at the native locus, capturing diverse variant effects on cellular HCM-relevant phenotypes. Our massively parallel splicing assay identified novel splice-disrupting variants. Integration of functional assays revealed that decreased MYBPC3 abundance is a key driver of HCM-related phenotypes. In parallel, downregulation of protein degradation was observed as a compensatory response to MYBPC3 loss of function, and novel disease mechanisms were identified for missense variants near a critical binding domain, underscoring their contribution to pathogenesis. Bayesian estimates of variant effects enable the reclassification of clinical variants. ConclusionsThis work provides a platform for extending genome engineering in iPSCs to multiplexed assays of variant effects across diverse disease-relevant cellular phenotypes, enhancing the understanding of variant pathogenicity and uncovering novel biological mechanisms that could inform therapeutic strategies.

genetics↗

bioRxiv2025

Detailed tandem repeat allele profiling in 1,027 long-read genomes reveals genome-wide patterns of pathogenicity

Short tandem repeat (STR) instability is a major cause of disease association, yet their full length-distributions and sequence content have been difficult to resolve with short-read sequencing. By analyzing long-read sequencing genomes from 2,645 participants of the All of Us Research Program, we establish a comprehensive STR resource of 23 billion alleles covering a catalog of 4.4 million loci. We find that known disease-associated STR loci exhibit markedly elevated allelic variability relative to genome-wide distributions, which is most pronounced when based on the length of uninterrupted, pure repeat motifs (Odds Ratio: 244, p=1.62e-29). We establish the Pure Length Variability Index (PLVI) as a measure of this instability, which is robust across ancestries and replicated in 500 samples from the 1000 Genomes Project (Odds Ratio: 84, p=2.72e-28). To illustrate, we identify 55 unstable coding CAG and 5-UTR CGG STR loci with this metric, 60% of which have not been associated with disease. From this set, we document potential pathogenic repeat expansions for FAM193B and EP400 by integrating PLVI with single-genome length outlier analysis. These data establish a population-scale framework for STR discovery in rare and common diseases using long-read sequencing cohorts.

genomics↗

bioRxiv2023

Loss of Mitochondrial Enoyl CoA Reductase causes elevated ceramide levels and impairs iron metabolism

In most eukaryotic cells fatty acid synthesis occurs in the cytoplasm as well as in mitochondria. However, the relative contribution of mitochondrial fatty acid synthesis (mtFAS) to the cellular lipidome of metazoans is ill-defined. Hence, we studied the function of the fly Mitochondria enoyl CoA reductase (Mecr), the enzyme required for the last step of mtFAS. Loss of mecr causes lethality while neuronal loss leads to progressive neurological defects. We observe an elevated level of ceramides, a defect in Fe-S cluster biogenesis and increased iron levels in mecr mutants. Reducing the levels of either iron or ceramide suppresses the neurodegenerative phenotypes indicating that increased ceramides and iron metabolism are interrelated and play an important role in the pathogenesis. Mutations in human MECR cause pediatric-onset neurodegeneration and patient-derived fibroblasts display similar elevated ceramide levels and impaired iron homeostasis. In summary, this study shows an as-yet-unidentified role of mecr/MECR in ceramide and iron metabolism providing a mechanistic link between mtFAS and neurodegeneration.

neuroscience↗

bioRxiv2023

RExPRT: a machine learning tool to predict pathogenicity of tandem repeat loci

Tandem repeats (TRs) are polymorphic sequences of DNA that are composed of repeating units of motifs, whose lengths can vary depending on the type of TR. Expansions of TRs are responsible for approximately 50 monogenic diseases, compared to over 4,300 disease causing genes disrupted by single nucleotide variants and small indels. It appears thus reasonable to expect the discovery of additional pathogenic repeat expansions, which has the potential of significantly narrowing the current diagnostic gap in many diseases. Recently, short and long-read whole genome sequencing with the use of advanced bioinformatics tools, have identified a growing number of TR expansions in the human population. The majority of these loci are expanded in <1% of genomes. Categorizing and prioritizing such TR loci is a growing challenge to human genomic studies. We present a first-in-class machine learning tool, RExPRT (Repeat EXpansion Pathogenicity pRediction Tool), which is designed to distinguish pathogenic from benign TR expansions. Leave-one-out cross validation results demonstrated that an ensemble approach comprised of support vector machines (SVM) and extreme gradient boosted decision tree (XGB) classify TRs with a precision of 92% and a recall of 90%. Further validation of RExPRT on unseen test data demonstrate a similar precision of 86%, and a recall of 60%. RExPRTs high precision in particular, will be of significant value to large-scale discovery studies, which require the prioritization of promising candidate loci for time-consuming and costly functional follow-up studies. Application of RExPRT to ~800,000 TRs in the reference genome identified ~30,000 TRs that would be likely pathogenic upon expansion. Thus, RExPRT establishes a foundation for the application of machine learning approaches to categorize the pathogenicity of tandem repeat loci.

bioinformatics↗

bioRxiv2023

The mitochondrial multi-omic response to exercise training across tissues

Mitochondria are adaptable organelles with diverse cellular functions critical to whole-body metabolic homeostasis. While chronic endurance exercise training is known to alter mitochondrial activity, these adaptations have not yet been systematically characterized. Here, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) mapped the longitudinal, multi-omic changes in mitochondrial analytes across 19 tissues in male and female rats endurance trained for 1, 2, 4 or 8 weeks. Training elicited substantial changes in the adrenal gland, brown adipose, colon, heart and skeletal muscle, while we detected mild responses in the brain, lung, small intestine and testes. The colon response was characterized by non-linear dynamics that resulted in upregulation of mitochondrial function that was more prominent in females. Brown adipose and adrenal tissues were characterized by substantial downregulation of mitochondrial pathways. Training induced a previously unrecognized robust upregulation of mitochondrial protein abundance and acetylation in the liver, and a concomitant shift in lipid metabolism. The striated muscles demonstrated a highly coordinated response to increase oxidative capacity, with the majority of changes occurring in protein abundance and post-translational modifications. We identified exercise upregulated networks that are downregulated in human type 2 diabetes and liver cirrhosis. In both cases HSD17B10, a central dehydrogenase in multiple metabolic pathways and mitochondrial tRNA maturation, was the main hub. In summary, we provide a multi-omic, cross-tissue atlas of the mitochondrial response to training and identify candidates for prevention of disease-associated mitochondrial dysfunction.

molecular biology↗

bioRxiv2020

Mono- and bi-allelic protein truncating variants in alpha-actinin 2 cause cardiomyopathy through distinct mechanisms

Alpha-actinin 2 (ACTN2) anchors actin within cardiac sarcomeres. The mechanisms linking ACTN2 mutations to myocardial disease phenotypes are unknown. Here, we characterize patients with novel ACTN2 mutations to reveal insights into the physiological function of ACTN2. Patient-derived iPSC-cardiomyocytes harboring ACTN2 protein-truncating variants were hypertrophic, displayed sarcomeric structural disarray, impaired contractility, and aberrant Ca2+-signaling. In heterozygous indel cells, the truncated protein incorporates into cardiac sarcomeres, leading to aberrant Z-disc structure. In homozygous stop-gain cells, affinity-purification mass spectrometry reveals an intricate ACTN2 interactome with sarcomere and sarcolemma-associated proteins. Loss of the C-terminus of ACTN2 disrupts interaction with ACTN1 and GJA1, two sarcolemma-associated proteins, that may lead to the clinical arrhythmic and relaxation defects. The causality of the stop-gain mutation was verified using CRISPR-Cas9 gene editing. Together, these data advance our understanding of the role of ACTN2 in the human heart and establish recessive inheritance of ACTN2 truncation as causative of disease.

genetics↗

bioRxiv2019

Differential response trajectories to acute exercise in blood and muscle

A physically active lifestyle is essential for maintaining health, and is a powerful way to prevent chronic disease. However, the molecular mechanisms that drive exercise adaptation and transduce its beneficial effects, are incompletely understood. Here, we combined data from 49 studies that measured the whole transcriptome in humans before and after exercise to provide the power to draw novel observations not seen in any individual study alone. The resulting curated and standardized resource includes samples from skeletal muscle (n=1,260) and blood (n=726) in response to endurance or resistance exercise and training. Using a linear mixed effects meta-regression model selection strategy, we detected specific time patterns and novel regulatory modulators of the acute exercise response. Acute and long term responses to exercise were transcriptionally distinct. Exercise induced a more pronounced inflammatory response in skeletal muscle of older individuals. We identified multiple sex-specific response genes, where MTMR3 is a novel exercise-regulated gene. These results deepen our understanding of the transcriptional responses to exercise and provide a powerful resource for future research efforts in exercise physiology and medicine.

physiology↗

bioRxiv2019

De novo EIF2AK1 and EIF2AK2 variants are associated with developmental delay, leukoencephalopathy, and neurologic decompensation

EIF2AK1 and EIF2AK2 encode members of the Eukaryotic Translation Initiation Factor 2 Alpha Kinase (EIF2AK) family that inhibits protein synthesis in response to physiologic stress conditions. EIF2AK2 is also involved in innate immune response and the regulation of signal transduction, apoptosis, cell proliferation, and differentiation. Despite these findings, human disorders associated with deleterious variants in EIF2AK1 and EIF2AK2 have not been reported. Here, we describe the identification of eight unrelated individuals with heterozygous de novo missense variants in EIF2AK1 (1/8) or EIF2AK2 (7/8). Features seen in these eight individuals include white matter alterations (8/8), developmental delay (8/8), impaired language (8/8), cognitive impairment (7/8), ataxia (6/8), dysarthria in probands with verbal ability (6/6), hypotonia (6/8), hypertonia (5/8), and involuntary movements (3/8). Individuals with EIF2AK2 variants also exhibit neurological regression in the setting of febrile illness or infection. We use mammalian cell lines and patient-derived fibroblasts to further confirm the pathogenicity of variants in these genes and found reduced kinase activity. EIF2AKs phosphorylate Eukaryotic Translation Initiation Factor 2 Subunit 1, (EIF2S1, also known as EIF2), which then inhibits EIF2B activity. Deleterious variants in genes encoding EIF2B proteins cause childhood ataxia with central nervous system hypomyelination/vanishing white matter disease (CACH/VWM), a leukoencephalopathy characterized by neurologic regression in the setting of febrile illness and other stressors. Our findings indicate that EIF2AK2 missense variants cause a neurodevelopmental syndrome that may share phenotypic and pathogenic mechanisms with CACH/VWM.

genetics↗

bioRxiv2019

Machine learning-based detection of insertions and deletions in the human genome

Insertions and deletions (indels) make a critical contribution to human genetic variation. While indel calling has improved significantly, it lags dramatically in performance relative to single-nucleotide variant calling, something of particular concern for clinical genomics where larger scale disruption of the open reading frame can commonly cause disease. Here, we present a machine learning-based approach to the detection of indel breakpoints called Scotch. This novel approach improves sensitivity to larger variants dramatically by leveraging sequencing metrics and signatures of poor read alignment. We also introduce a meta-analytic indel caller, called Metal, that performs a "smart intersection" of Scotch and currently available tools to be maximally sensitive to large variants. We use new benchmark datasets and Sanger sequencing to compare Scotch and Metal to current gold standard indel callers, achieving unprecedented levels of precision and recall. We demonstrate the impact of these improvements by applying this tool to a cohort of patients with undiagnosed disease, generating plausible novel candidates in 21 out of 26 undiagnosed cases. We highlight the diagnosis of one patient with a 498-bp deletion in HNRNPA1 missed by traditional indel-detection tools.

bioinformatics↗

bioRxiv2019

Allele-specific silencing ameliorates restrictive cardiomyopathy due to a human myosin regulatory light chain mutation

BackgroundRestrictive cardiomyopathy (RCM) is a rare heart disease associated with mutations in sarcomeric genes and with phenotypic overlap with hypertrophic cardiomyopathy. There is no approved therapy. Here, we explore the potential of an interfering RNA (RNAi) therapeutic for a human sarcomeric mutation in MYL2 causative of restrictive cardiomyopathy in a mouse model. MethodsAAV9-M7.8L shRNA was selected from a pool of RNAi oligonucleotides containing the SNV in different positions to specifically target the mutated allele causative of RCM by FACS screening. Two groups of RLC-N47K transgenic mice were injected with a single dose of AAV9-M7.8L shRNA at 3 days of age and at 60 days of age. Mice were subjected to treadmill exercise and echocardiography after treatment to determine VO2max and left ventricular mass. At the end of treatment, heart, lung, liver and kidney tissue was harvested to determine viral tropism and for transcriptome and proteomic analysis. Cardiomyocytes were isolated for single cell studies. ResultsOne time injection of AAV9-M7.8L RNAi in 3-day-old humanized RLC mutant transgenic mice silenced the mutated allele (RLC-47K) with minimal effects on the normal allele (RLC-47N) assayed 16 weeks post-injection. AAV9-M7.8L RNAi suppressed the expression of hypertrophic biomarkers, reduced heart weight and attenuated a pathological increase in left ventricular mass (LVM). Single adult cardiac myocytes from mice treated with AAV9-M7.8L showed partial restoration of the maximal contraction velocity with marked reduction in hypercontractility as well as relaxation kinetics and improved time to maximal calcium reuptake velocity. In addition, cardiac stress protein biomarkers, such as calmodulin-dependent protein kinase II (CAMKII) and the transcription activator Brg1 were reduced suggesting recovery towards a healthy myocardium. Transcriptome analyses further revealed no significant changes of argonaute (AGO1, AGO2) and endoribonuclease dicer (DICER1) transcripts while endogenous microRNAs were preserved suggesting the RNAi pathway was not saturated. ConclusionsOur results show the feasibility, efficacy, and safety of RNAi therapeutics directed at human restrictive cardiomyopathy. This is a promising step towards targeted therapy for a prevalent human disease. Clinical PerspectiveWhat is new? O_LIRestrictive cardiomyopathy due to a mutation of human MYL2 modeled in cells and mice can be treated with RNA interference C_LIO_LIReduction of disease-causing allele improves function at the cellular and organ level C_LIO_LIOff target effects evaluated and not found to be significant C_LI What are the clinical implications? O_LIAllele-specific RNA silencing of human alleles may be effective in treating inherited restrictive cardiomyopathy C_LIO_LIRNA therapies targeting individual mutations may need to be developed prior to consideration of clinical translation C_LI

molecular biology↗

bioRxiv2018

Identification of rare-disease genes in diverse undiagnosed cases using whole blood transcriptome sequencing and large control cohorts

RNA sequencing (RNA-seq) is a complementary approach for Mendelian disease diagnosis for patients in whom exome-sequencing is not informative. For both rare neuromuscular and mitochondrial disorders, its application has improved diagnostic rates. However, the generalizability of this approach to diverse Mendelian diseases has yet to be evaluated. We sequenced whole blood RNA from 56 cases with undiagnosed rare diseases spanning 11 diverse disease categories to evaluate the general application of RNA-seq to Mendelian disease diagnosis. We developed a robust approach to compare rare disease cases to existing large sets of RNA-seq controls (N=1,594 external and N=31 family-based controls) and demonstrated the substantial impacts of gene and variant filtering strategies on disease gene identification when combined with RNA-seq. Across our cohort, we observed that RNA-seq yields a 8.5% diagnostic rate. These diagnoses included diseases where blood would not intuitively reflect evidence of disease. We identified RARS2 as an under-expression outlier containing compound heterozygous pathogenic variants for an individual exhibiting profound global developmental delay, seizures, microcephaly, hypotonia, and progressive scoliosis. We also identified a new splicing junction in KCTD7 for an individual with global developmental delay, loss of milestones, tremors and seizures. Our study provides a broad evaluation of blood RNA-seq for the diagnosis of rare disease.

genomics↗

bioRxiv2016

Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort

BackgroundThe ability to measure activity and physiology through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown.\n\nObjectiveTo assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework.\n\nMethodsWe evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 {+/-} 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination.\n\nResultsDevices reported the lowest error for cycling and the highest for walking. Device error was higher for males,greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest.\n\nConclusionsMost wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).\n\nAbbreviations

bioinformatics↗