mtDNA Single-Nucleotide Variants Associated with Type 2 Diabetes

Type 2 diabetes (T2D) is a chronic systemic disease with a complex etiology, characterized by insulin resistance and mitochondrial dysfunction in various cell tissues. To explore this relationship, we conducted a secondary analysis of complete mtDNA sequences from 1261 T2D patients and 1105 control individuals. Our findings revealed significant associations between certain single-nucleotide polymorphisms (SNPs) and T2D. Notably, the variants m.1438A>G (rs2001030) (controls: 32 [27.6%], T2D: 84 [72.4%]; OR: 2.46; 95%CI: 1.64-3.78; p < 0.001), m.14766C>T (rs193302980) (controls: 498 [36.9%], T2D: 853 [63.1%]; OR: 2.57, 95%CI: 2.18-3.04, p < 0.001), and m.16519T>C (rs3937033) (controls: 363 [43.4%], T2D: 474 [56.6%]; OR: 1.24, 95%CI: 1.05-1.47, p = 0.012) were significantly associated with the likelihood of developing diabetes. The variant m.16189T>C (rs28693675), which has been previously documented in several studies across diverse populations, showed no association with T2D in our analysis (controls: 148 [13.39] T2D: 171 [13.56%]; OR: 1.03; 95%CI: 0.815-1.31; p = 0.83). These results provide evidence suggesting a link between specific mtDNA polymorphisms and T2D, possibly related to association rules, topological patterns, and three-dimensional conformations associated with regions where changes occur, rather than specific point mutations in the sequence.

Risk factors and association of body composition components for lumbar disc herniation in Northwest, Mexico

The goal of this study was to investigate the association of body composition components and to elucidate whether any of these components is a risk factor for Lumbar Disc Herniation (LDH). The group of study consisted of 90 adults involved in a physical activity program due to overweight and obesity. 19 adults with medical diagnostic through Magnetic Resonance Imaging with LDH. Body composition data was obtained with a bioelectrical impedance analyzer. Descriptive statistics and principal components analysis permitted to analyze the information's structure and to visualize information clusters. A logistic regression analysis allowed us to find the association between some of the variables of body composition with LDH. The Degree of Obesity, Body Mass Index, Visceral Fat Area and the Abdominal Circumference resulted associated (P values of 0.0388, 0.0171, 0.0055 and 0.0032, respectively). The application of Odd Ratio allowed us to declare the Visceral Fat Area and Abdominal Circumference as risk factors to develop Lumbar Disk Herniation. Our results provide a new record for future studies, and support for prescription of physical activity and changes in diet, to correct or prevent the development of LDH in the population of Baja California.

Benefit of oxytocin released by cervix stimulation in Mexican Holstein cattle

Objective:

The aim of this research is to investigate the relationship level of oxytocin released and the tactile stimulation of the cervix in Holstein cattle from the northwestern arid regions in México.

Materials and Methods:

The cervixes of 10 Holstein Friesian dairy cows in mid-lactation were manually stimulated for 60 sec. Oxytocin released in the blood was analyzed before and after stimulation. The enzyme-linked immunosorbent assay was used in the analysis to make oxytocin detectable by spectrometry techniques and by converting the luminescence absorbance of each sample into pg per mol.

Results:

The study revealed that tactile stimulation of the cervix increased oxytocin levels. The highest increase in oxytocin level was 10,940.8222 pg/mol, while the lowest increase in oxytocin level was 1,830.94254 pg/mol. Besides, the milk production by tactile stimulation of the cervix had a higher milk yield and a p-value of 9.4 × 10⁻⁴ (p < 0.05) in comparison to the monthly average without tactile stimulation.

Conclusion:

Tactile stimulation of the cervix activates the Ferguson reflex and increases the oxytocin released in the blood and increases the milk released from the alveolar glands.

Genome-wide identification of copy number variations in Holstein cattle from Baja California, Mexico, using high-density SNP genotyping arrays

Copy number variations (CNVs) are an important source of genomic structural variation, and can be used as markers to investigate phenotypic and economic traits. CNVs also have functional effects on gene expression and can contribute to disease susceptibility in mammals. Currently, single nucleotide polymorphism genotyping arrays (SNP chips) are the technology of choice for identifying CNV variations. Microarray technologies have recently been used to study the bovine genome. The objective of the present study was to develop CNVs in Holstein cows from the Northwest of Mexico using the Affymetrix Axiom Genome-Wide BOS 1 Array, which assays 648,315 SNPs and provides a wide coverage for genome-wide studies. We applied the two most widely used algorithms for the discovery of CNVs (PennCNV and QuantiSNP) and found 56 CNV regions (CNVRs) representing 0.33% of the bovine genome (8.46 Mb). These CNVRs ranged from 1.5 to 970.8 kb with an average length of 151 kb. They involved 103 genes and showed a 28% overlap with CNVRs already reported. Of the 56 CNVRs found, 20 were novel. In this study we present the first genomic analysis of CNVs in Mexican cattle using high-density SNP data. Our results provide a new reference basis for future genomic variation and association studies between CNVs and phenotypes, especially in Mexican cattle.

High density LD-based structural variations analysis in cattle genome

Genomic structural variations represent an important source of genetic variation in mammal genomes, thus, they are commonly related to phenotypic expressions. In this work, ∼770,000 single nucleotide polymorphism genotypes from 506 animals from 19 cattle breeds were analyzed. A simple LD-based structural variation was defined, and a genome-wide analysis was performed. After applying some quality control filters, for each breed and each chromosome we calculated the linkage disequilibrium (r²) of short range (≤100 Kb). We sorted SNP pairs by distance and obtained a set of LD means (called the expected means) using bins of 5 Kb. We identified 15,246 segments of at least 1 Kb, among the 19 breeds, consisting of sets of at least 3 adjacent SNPs so that, for each SNP, r² within its neighbors in a 100 Kb range, to the right side of that SNP, were all bigger than, or all smaller than, the corresponding expected mean, and their P-value were significant after a Benjamini-Hochberg multiple testing correction. In addition, to account just for homogeneously distributed regions we considered only SNPs having at least 15 SNP neighbors within 100 Kb. We defined such segments as structural variations. By grouping all variations across all animals in the sample we defined 9,146 regions, involving a total of 53,137 SNPs; representing the 6.40% (160.98 Mb) from the bovine genome. The identified structural variations covered 3,109 genes. Clustering analysis showed the relatedness of breeds given the geographic region in which they are evolving. In summary, we present an analysis of structural variations based on the deviation of the expected short range LD between SNPs in the bovine genome. With an intuitive and simple definition based only on SNPs data it was possible to discern closeness of breeds due to grouping by geographic region in which they are evolving.