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PubMed2001

Linkage analysis of a complex pedigree with severe bipolar disorder, using a Markov chain Monte Carlo method.

Recently developed algorithms permit nonparametric linkage analysis of large, complex pedigrees with multiple inbreeding loops. We have used one such algorithm, implemented in the package SimWalk2, to reanalyze previously published genome-screen data from a Costa Rican kindred segregating for severe bipolar disorder. Our results are consistent with previous linkage findings on chromosome 18 and suggest a new locus on chromosome 5 that was not identified using traditional linkage analysis.

Algorithms↗

PubMed2001

Seven regions of the genome show evidence of linkage to type 1 diabetes in a consensus analysis of 767 multiplex families.

Type 1 diabetes (T1D) is a genetically complex disorder of glucose homeostasis that results from the autoimmune destruction of the insulin-secreting cells of the pancreas. Two previous whole-genome scans for linkage to T1D in 187 and 356 families containing affected sib pairs (ASPs) yielded apparently conflicting results, despite partial overlap in the families analyzed. However, each of these studies individually lacked power to detect loci with locus-specific disease prevalence/sib-risk ratios (lambda(s)) <1.4. In the present study, a third genome scan was performed using a new collection of 225 multiplex families with T1D, and the data from all three of these genome scans were merged and analyzed jointly. The combined sample of 831 ASPs, all with both parents genotyped, provided 90% power to detect linkage for loci with lambda(s) = 1.3 at P=7.4x10(-4). Three chromosome regions were identified that showed significant evidence of linkage (P<2.2x10(-5); LOD scores >4), 6p21 (IDDM1), 11p15 (IDDM2), 16q22-q24, and four more that showed suggestive evidence (P<7.4x10(-4), LOD scores > or =2.2), 10p11 (IDDM10), 2q31 (IDDM7, IDDM12, and IDDM13), 6q21 (IDDM15), and 1q42. Exploratory analyses, taking into account the presence of specific high-risk HLA genotypes or affected sibs' ages at disease onset, provided evidence of linkage at several additional sites, including the putative IDDM8 locus on chromosome 6q27. Our results indicate that much of the difficulty in mapping T1D susceptibility genes results from inadequate sample sizes, and the results point to the value of future international collaborations to assemble and analyze much larger data sets for linkage in complex diseases.

Adolescent↗

PubMed2025

Unveiling metabolic pathways in the hyperglycemic bone: bioenergetic and proteomic analysis of the bone tissue exposed to acute and chronic high glucose.

BACKGROUND: Bone fragility due to poor glycemic control is a recognized complication of diabetes, but the mechanisms underlying diabetic bone disease remain poorly understood. Despite the importance of bioenergetics in tissue functionality, the impact of hyperglycemia on bone bioenergetics has not been previously investigated. OBJECTIVE: To determine the effects of high glucose exposure on energy metabolism and structural integrity in bone tissue using an ex vivo organotypic culture model of embryonic chick femur. METHODS: Femora from eleven-day-old Gallus gallus embryos were cultured for eleven days under physiological glucose conditions (5.5 mM, NG), chronic high glucose exposure (25 mM, HG-C), or acute high glucose exposure (25 mM, HG-A). Bioenergetic assessments (Seahorse assays), proteomic analysis (liquid chromatography-mass spectrometry), histomorphometric and microtomographic evaluations, and oxidative stress measurements (carbonyl content assay) were performed. Statistical analyses were conducted using IBM® SPSS® Statistics (v26.0). The Mann-Whitney nonparametric test was used for group comparisons in microtomographic analysis, ALP activity, and carbonyl content assays. For Seahorse assay results, ANOVA with Tukey's post-hoc test was applied after confirming data homoscedasticity with Levene's test. RESULTS: Chronic high glucose exposure reduced bone mineral deposition, altered histomorphometric indices, and suppressed key osteochondral development regulators. Acute high glucose exposure enhanced glycolysis and oxidative phosphorylation, while chronic exposure caused oxygen consumption uncoupling, increased ROS generation, and downregulated mitochondrial proteins critical for bioenergetics. Elevated oxidative stress was confirmed in the chronic high glucose group. CONCLUSION: Chronic high glucose exposure disrupted bone bioenergetics, induced mitochondrial dysfunction, and compromised bone structural integrity, emphasizing the metabolic impact of hyperglycemia in diabetic bone disease.

Animals↗

PubMed2026

An end-to-end computational framework for "Record-seq" transcriptional recording data.

MOTIVATION: Record-seq captures cumulative transcriptional activity over time in engineered Escherichia coli by integrating cellular RNA-derived spacer sequences into clustered regularly interspaced short palindromic repeats (CRISPR) arrays, which are read out by sequencing. Unlike the approximately uniform transcript sampling of RNA-seq, Record-seq records biological signal as spacers sampled by the CRISPR spacer acquisition machinery. Consequently, standard RNA-seq analysis strategies are not directly applicable, limiting sensitivity and interpretability. Our previous pipeline addressed these challenges only partially, retained inherited RNA-seq assumptions, and had limited algorithmic efficiency. RESULTS: Here, we present an end-to-end computational framework for Record-seq data. To address the primary computational bottleneck of spacer sequence extraction, we implemented a wavefront alignment approach for efficient quasi-local pattern matching, achieving an approximately 30-fold speedup. We introduce transcription unit-based feature counting as an alternative to gene-body quantification to better represent prokaryotic transcription and increase statistical power by capturing signal from untranslated regions, which are spacer acquisition hotspots. For downstream analyses, we incorporate multiple normalization strategies and a nonparametric differential expression testing framework designed for sparse datasets. Further, we analyze spacer acquisition patterns and train sequence-based neural models that predict acquisition propensity from genomic sequence and annotations, providing a framework for assessing whether acquisition rules generalize as Record-seq is extended to new microbial hosts. AVAILABILITY AND IMPLEMENTATION: The primary analysis workflow, the recoRdseq package, acquisition modeling repository, and relevant data are all linked at https://github.com/plattlab/Record-seq-Framework. Acquisition models and training data are on Zenodo at https://doi.org/10.5281/zenodo.18891434.

Escherichia coli↗

PubMed2026

From Peaks to Power: Systematic Evaluation of Chromatographic Sampling Reveals Determinants of Quantification and Biological Discovery in DIA Proteomics.

Modern DIA proteomics increasingly emphasizes throughput and depth for large-cohort studies, but methods are often optimized using proxy metrics that can mask losses in quantifiable signal and statistical power. Here, we evaluate how data points per peak and other chromatographic features jointly contribute to quantification and downstream biological discovery. Using a matrix-matched calibration curve dataset, we checked how the number of data points per peak (DPPP) affects the limits of detection and quantification (LOD/LOQ). Reduced DPPP minimally affected LOD but substantially degraded LOQ. Feature modeling and nonparametric association analyses identified precursor peak area as the strongest feature-level predictor of LOQ, whereas DPPP showed weaker and context-dependent effects. Simulations of chromatographic peak integration recapitulated these trends, showing that increased sampling primarily improves integration precision, while quantitative accuracy is strongly governed by peak height and peak shape. Finally, when comparing 20 cancer vs 20 control plasma samples processed with Seer Proteograph, the decrease in DPPP led to a loss of statistical significance for proteins with low-abundance precursors. These findings argue that DIA optimization should prioritize LOQ and statistical power metrics─not identifications alone─by balancing sampling density with chromatographic peak height and quality to maximize useful biological signal.

Proteomics↗

PubMed2026

The Role of Genetic Variation in Phenotypic Variability in Loeys-Dietz Syndrome.

BACKGROUND: Loeys-Dietz syndrome (LDS) is a heritable connective tissue disorder caused by pathogenic variants in genes of the transforming growth factor-β (TGF-β) signaling pathway. Although genotype-phenotype correlations have been suggested, comprehensive comparative data across LDS subtypes remain limited. Improved understanding of these correlations is essential to guide individualized surveillance and management strategies. METHODS: We conducted a retrospective cohort study of adults with genetically confirmed LDS evaluated between 2018 and 2024 across Mayo Clinic sites. Patients with pathogenic, likely pathogenic, or suspicious variants in TGFBR1, TGFBR2, or SMAD3 were included. Clinical characteristics, physical examination findings, cardiovascular and noncardiovascular manifestations, surgical interventions, and mortality were compared across genotypes. Categorical variables were analyzed using chi-square tests and continuous variables using parametric or nonparametric methods as appropriate. RESULTS: A total of 93 patients were included (29 TGFBR1, 33 TGFBR2, 31 SMAD3). Demographics and mortality did not differ significantly between groups. Patients with TGFBR1 and TGFBR2 demonstrated trends toward higher rates of ascending aortic aneurysm and aortic dissection compared with SMAD3 patients, though these differences were not statistically significant. Renal artery aneurysms were significantly more common in TGFBR1 patients (13.8%, p = 0.010). SMAD3 patients had significantly higher rates of mitral regurgitation (54.8%, p = 0.04), peripheral neuropathy (29.0%, p = 0.018), and trends toward increased atrial fibrillation and osteoarthritis. A novel association was identified between TGFBR1 variants and migraine, which was significantly more prevalent in this group (62.1%, p = 0.017). The rates of major cardiovascular surgical interventions were high and comparable across all genotypes. CONCLUSION: Distinct genotype-phenotype associations exist among LDS subtypes. TGFBR1 and TGFBR2 variants are associated with a greater burden of aggressive vascular disease, whereas SMAD3 variants are linked to mitral valve disease, peripheral neuropathy, and osteoarthritis. We also identified a novel association between TGFBR1 genotype and migraine. These findings reinforce the importance of comprehensive genetic testing to inform personalized surveillance and management strategies in LDS.

Humans↗

PubMed2026

Mealtime satisfaction in public nursing homes: Associations with sensory, foodservice, and dining-room environment factors.

Satisfaction with meals is commonly used to assess how meals are experienced in nursing homes (NH), although limited evidence compares breakfast, lunch, and dinner within a unified analytical framework. This study examined the sensory and contextual factors associated with satisfaction across meals in public NH. A cross-sectional observational study was conducted using structured interviews with 290 residents aged ≥60 years (median 85 years; Q1-Q3: 81-88; 63.1% women) from 19 facilities in Galicia, Spain. Overall satisfaction and 12 factors related to sensory attributes of the food, foodservice characteristics, and dining-room environment were assessed using a 5-point Likert scale. Descriptive analyses used medians and quartiles, and group comparisons were performed using nonparametric tests. Three multivariable linear regression models, one per meal, were estimated including all factors simultaneously. In adjusted models, the largest standardized coefficients were observed for taste (lunch: β = 0.366; P < 0.001), food temperature at serving (dinner: β = 0.319; P < 0.001), and menu variety (breakfast: β = 0.301; P < 0.001). Taste, food temperature at serving, menu variety, and meal schedule showed statistically significant coefficients in all models. Overall satisfaction was lower at dinner (29.0% ≥ 4) than at breakfast (34.8%) and lunch (34.5%) (P = 0.003). Selected dining-room environment factors showed significant coefficients in meal-specific models. Mealtime satisfaction was mainly associated with sensory and contextual factors related to how meals are perceived. Lower satisfaction at dinner suggests this mealtime as a relevant context for understanding variations in meal perception in NH residents.

Humans↗