Biology subjects

Reich, C.

Publications and source records attributed to Reich, C..

4 recordsLinked to original sources

bioRxiv2026

Toward routine health phenotyping: High-throughput prediction of metabolic, immune, and inflammatory biomarkers from milk mid-infrared spectroscopy in early-lactation dairy cows

This study evaluated the potential of milk mid-infrared (MIR) spectroscopy, combined with routinely available on-farm variables, for predicting serum metabolic, immune, and inflammatory biomarkers in early-lactation cows. Data included 5,936 blood samples from 4,442 cows across 23 Australian dairy herds, with paired milk MIR spectra and serum measurements for up to 14 biomarkers. Prediction models were developed using partial least squares regression and evaluated using nested 10-fold random cross-validation and leave-one-herd-out validation. The results show that while basic herd-test data, including milk fat, protein, and lactose concentration, as well as on-farm variables, including DIM, calving age, breed, and herd could predict serum biomarkers, combining MIR spectra with these on-farm variables produced the best overall performance. In random cross-validation, blood urea nitrogen (BUN) was predicted most accurately (R2 = 0.78), while {beta}-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) showed moderate accuracy (R2 = 0.56 and 0.44, respectively). BUN also showed the strongest external validation performance, with leave-one-herd-out R2 = 0.58 and comparable accuracy for predicting records collected after 70 days in milk (R2 = 0.65). BHB and NEFA had moderate leave-one-herd-out accuracy but did not transfer beyond early lactation. Most other biomarkers showed low or inconsistent external validation performance. Overall, MIR spectroscopy combined with on-farm variables shows promise for routine prediction of BUN, BHB and NEFA, which can be used for monitoring and genetic evaluation of, for example, ketosis and energy deficit. Initial random cross-validation results for glucose, bilirubin and cholesterol were promising, but more data is needed to improve the prediction accuracy and robustness of the predictions. HighlightsO_LIMilk MIR can predict several serum biomarkers in early-lactation dairy cows. C_LIO_LIMIR-predicted blood urea nitrogen shows the greatest accuracy and robustness. C_LIO_LIMIR-predicted {beta}-hydroxybutyrate and nonesterified fatty acids show moderate accuracy. C_LIO_LIMost mineral, hepatic, and inflammatory biomarkers had limited accuracy. C_LIO_LIRoutine MIR phenotyping is most promising for BUN, BHB, and NEFA. C_LI SummaryMilk mid-infrared (MIR) spectroscopy and on-farm variables are evaluated as a high-throughput tool to predict health-related serum biomarkers in early-lactation dairy cows. The data include 5,936 paired blood and milk samples from 4,442 cows across 23 Australian dairy herds and up to 14 serum biomarkers. Prediction models are developed using partial least squares regression with nested random cross-validation and leave-one-herd-out validation. Blood urea nitrogen (BUN) shows the greatest and most transferable prediction accuracy across herds and lactation stages. {beta}-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) are predicted with moderate accuracy, but only during early lactation. Random cross-validation results for glucose and bilirubin are promising, but larger datasets are needed for robust external validation. Most other mineral, hepatic, and inflammatory biomarkers show limited external prediction accuracy. These results indicate that MIR-based routine health phenotyping is most promising for BUN, BHB, and NEFA.

genetics↗

bioRxiv2025

Sarcomeric Remodelling in Human Heart Failure unraveled by single molecule long read sequencing

Dysregulation of alternative splicing - mediated by factors such as RBM20 or SLM2 - can affect proper gene isoform control disrupts gene isoform homeostasis and underpins severe cardiomyopathy in both animal models and patients. Although innovative therapies target various sarcomeric components, the impact of isoform switching in cardiac disease remains poorly understood. Here, we applied nanopore long-read sequencing to map the full-length transcriptome of left ventricular tissue from thirteen nonfailing controls, ten patients with dilated cardiomyopathy (DCM), and ten with ischemic cardiomyopathy (ICM). Our analysis identified 78,520 transcripts, 31% of which represent novel isoforms of known genes. Notably, the transcriptomes of DCM and ICM were largely indistinguishable, indicating that end-stage heart failure is characterized by a convergent isoform landscape, irrespective of disease etiology. Among 11 prototypical sarcomere genes, 10 displayed highly significant isoform shifts (p= 5.23x10-45 - 2.89x10-200). Focusing on tropomyosin, we observed that while the predominant cardiac gene TPM1 showed moderate up-regulation of its transcript isoforms, transcripts derived from TPM3--typically expressed at lower levels in the healthy heart--were markedly increased in heart failure.

genetics↗

bioRxiv2025

RBM20-variants induce distinct calcium handling and metabolic phenotypes in patient-specific stem cell models of dilated and non-compaction cardiomyopathy

Background and aimMutations in the splice regulator RBM20 account for [~]3 % of genetic cardiomyopathies. In particular, the highly conserved RS domain is a hotspot for disease-associated mutations. Previously, mutations at same amino acid position 634 in the hotspot RS-domain were found to cause dilated cardiomyopathy (DCM) with left ventricular non-compaction (R634L) or without (R634W), but the pathophysiological mechanisms that govern the heterogeneity in phenotype presentation remained unknown. Here, we identify the molecular events caused by the distinct RBM20 mutations from DCM and left-ventricular non-compaction (LVNC) using patient-specific stem cell models. MethodsWe generated induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) of one LVNC- and two DCM-patients harboring the RBM20-mutations R634L (LVNC) or R634W (DCM). We investigated alternative splicing activity, RBM20 localization, sarcomeric regularity, cAMP level, kinase-specific phosphorylation of key Ca2+ handling enzymes, physiological cardiac functions as Ca2+ homeostasis, and metabolic activity on a patient-specific cardiomyocyte level. Force generation was analyzed in patient-specific engineered myocardial tissues. Isogenic rescue and mutation insertion lines were generated by CRISPR/Cas9 technology to analyze the direct impact of the RBM20 mutations on the cardiac phenotype. ResultsWe observed common splicing aberrations for LVNC- and DCM-CM in TTN and RYR2, RBM20 cytoplasmatic accumulation and irregular sarcomeric structure. LVNC-CM harboring the RBM20-p.R634L variant show distinct molecular, cellular and functional impairments that manifest in CAMK2D, TRDN and IMMT mis-splicing. Splicing defects in LVNC-CM correlate with elevated systolic Ca2+ and faster Ca2+ kinetics with elevated cAMP levels and PLN-hyperphosphorylation. An increased metabolic activity and mitochondrial membrane potential support the hyperactive LVNC-CM. By contrast, DCM-CM (RBM20-p.R634W) distinctly present with decreased systolic Ca2+ and increased SR Ca2+leak but unchanged Ca2+ kinetics and metabolic activity. Both mutations lead to severely reduced force of contraction in engineered myocardium. CRISPR/Cas9 gene-edited isogenic control lines of both described RBM20 mutations in LVNC and DCM demonstrated the causative nature of the two mutations and their diverging effects. Further, L-type Ca2+ channel blockade by verapamil ameliorates the Ca2+ cycling and leakage phenotypes in LVNC- and DCM-CM. ConclusionWe show the first comparative iPSC-model of splice-defect-associated RBM20-dependent LVNC-p.R634L and DCM-p.R634W. We found shared and variant-specific phenotypes on a patient-specific level. Our data demonstrate that the different RBM20 mutations manifest in distinct molecular aberrations in alternative splicing and RBM20 cytoplasmic accumulation that convey various physiological impairments in structure, Ca2+ handling, metabolism and contractile force.

molecular biology↗

bioRxiv2019

Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits

Many genome variants shaping mammalian phenotype are hypothesized to regulate gene transcription and/or to be under selection. However, most of the evidence to support this hypothesis comes from human studies. Systematic evidence for regulatory and evolutionary signals contributing to complex traits in a different mammalian model is needed. Sequence variants associated with gene expression (eQTLs) and concentration of metabolites (mQTLs), and under histone modification marks in several tissues were discovered from multi-omics data of over 400 cattle. Variants under selection and evolutionary constraint were identified using genome databases of multiple species. These analyses defined 30 sets of variants and for each set we estimated the genetic variance the set explained across 34 complex traits in 11,923 bulls and 32,347 cows with 17,669,372 imputed variants. The per-variant trait heritability of these sets across traits was highly consistent (r>0.94) between bulls and cows. Based on the per-variant heritability, conserved sites across 100 vertebrate species and mQTLs ranked the highest, followed by eQTLs, young variants, those under histone modification marks and selection signatures. From these results, we defined a Functional-And-Evolutionary Trait Heritability (FAETH) score indicating the functionality and predicted heritability of each variant. In 7,551 Danish cattle, the high FAETH-ranking variants had significantly increased genetic variances and genomic prediction accuracies in 3 production traits compared to the low FAETH-ranking variants. The FAETH framework combines the information of gene regulation, evolution and trait heritability to rank variants and the publicly available FAETH data provides a set of biological priors for cattle genomic selection worldwide.

genomics↗