A Genome-Wide Approach To Drug Development For Fibrosis

Author(s):  
Jeff Braziunas ◽  
Matthew W. Parker ◽  
Mark Peterson ◽  
Karen Smith ◽  
Jon Michael Underwood ◽  
...  
2020 ◽  
Author(s):  
Sandra Paulina Smieszek ◽  
Mihael Polymeropoulos

Abstract BACKGROUND Animals are used as preclinical models for human diseases in drug development. Dogs, especially, are used in preclinical research to support the clinical safety evaluations during drug development. Comparisons of patterns of regions of homozygosity (ROH) and phenotypes between dog and human are not well known. We conducted a genome-wide homozygosity analysis (GWHA) in the human and the dog genomes.RESULTS We calculated ROH patterns across distinct human cohorts including the Amish, the 1000 genomes, Wellderly, Vanda 1 k genomes, and Alzheimer’s cohort. The Amish provided a large cohort of extended kinships allowing for in depth family oriented analyses. The remaining human cohorts served as statistical references. We then calculated ROH across different dog breeds with emphasis on the beagle - the preferred breed used in drug development. Out of five studied human cohorts we reported the highest mean ROH in the Amish population. We calculated the extent of the genome covered by ROH (FROH) (human 3.2 Gb, dog 2.5 Gb). Overall FROH differed significantly between the Amish and the 1000 genomes, and between the human and the beagle genomes. The mean FROH per 1 Mb was ~ 16 kb for Amish, ~ 0.6 kb for Vanda 1 k, and ~ 128 kb for beagles. This result demonstrated the highest degree of inbreeding in beagles, far above that of the Amish, one of the most inbred human populations. ROH can contribute to inbreeding depression if they contain deleterious variants that are fully or partially recessive.CONCLUSIONS The differences in ROH characteristics between human and dog genomes question the applicability of dog models in preclinical research, especially when the goal is to gauge the subtle effects on the organism’s physiology produced by candidate therapeutic agents. Importantly, there are huge differences in a subset of ADME genes, specifically cytochrome P450 family (CYPs), constituting major enzymes involved in drug metabolism. We should use caution when generalizing from dog to human, even if human and beagle are relatively close species phylogenetically


2020 ◽  
Author(s):  
SP. Smieszek ◽  
MP. Polymeropoulos

AbstractAnimals are used as preclinical models for human diseases in drug development. Dogs, especially, are used in preclinical research to support the clinical safety evaluations during drug development. Comparisons of patterns of regions of homozygosity (ROH) and phenotypes between dog and human are not well known. We conducted a genome-wide homozygosity analysis (GWHA) in the human and the dog genomes.We calculated ROH patterns across distinct human cohorts including the Amish, the 1000 genomes, Wellderly, Vanda 1k genomes, and Alzheimer’s cohort. The Amish provided a large cohort of extended kinships allowing for in depth family oriented analyses. The remaining human cohorts served as statistical references. We then calculated ROH across different dog breeds with emphasis on the beagle - the preferred breed used in drug development.Out of five studied human cohorts we reported the highest mean ROH in the Amish population. We calculated the extent of the genome covered by ROH (FROH) (human 3.2Gb, dog 2.5Gb). Overall FROH differed significantly between the Amish and the 1000 genomes, and between the human and the beagle genomes. The mean FROH per 1Mb was ∼16kb for Amish, ∼0.6kb for Vanda 1k, and ∼128kb for beagles. This result demonstrated the highest degree of inbreeding in beagles, far above that of the Amish, one of the most inbred human populations.ROH can contribute to inbreeding depression if they contain deleterious variants that are fully or partially recessive. The differences in ROH characteristics between human and dog genomes question the applicability of dog models in preclinical research, especially when the goal is to gauge the subtle effects on the organism’s physiology produced by candidate therapeutic agents. Importantly, there are huge differences in a subset of ADME genes, specifically cytochrome P450 family (CYPs), constituting major enzymes involved in drug metabolism. We should hesitate to generalize from dog to human, even if human and beagle are relatively close species phylogenetically


2014 ◽  
Vol 226 (03) ◽  
Author(s):  
F Ponthan ◽  
D Pal ◽  
J Vormoor ◽  
O Heidenreich
Keyword(s):  

2007 ◽  
Vol 30 (4) ◽  
pp. 86
Author(s):  
M. Lanktree ◽  
J. Robinson ◽  
J. Creider ◽  
H. Cao ◽  
D. Carter ◽  
...  

Background: In Dunnigan-type familial partial lipodystrophy (FPLD) patients are born with normal fat distribution, but subcutaneous fat from extremities and gluteal regions are lost during puberty. The abnormal fat distribution leads to the development of metabolic syndrome (MetS), a cluster of phenotypes including hyperglycemia, dyslipidemia, hypertension, and visceral obesity. The study of FPLD as a monogenic model of MetS may uncover genetic risk factors of the common MetS which affects ~30% of adult North Americans. Two molecular forms of FPLD have been identified including FPLD2, resulting from heterozygous mutations in the LMNA gene, and FPLD3, resulting from both heterozygous dominant negative and haploinsufficiency mutations in the PPARG gene. However, many patients with clinically diagnosed FPLD have no mutation in either LMNA or PPARG, suggesting the involvement of additional genes in FPLD etiology. Methods: Here, we report the results of an Affymetrix 10K GeneChip microarray genome-wide linkage analysis study of a German kindred displaying the FPLD phenotype and no known lipodystrophy-causing mutations. Results: The investigation identified three chromosomal loci, namely 1q, 3p, and 9q, with non-parametric logarithm of odds (NPL) scores >2.7. While not meeting the criteria for genome-wide significance, it is interesting to note that the 1q and 3p peaks contain the LMNA and PPARG genes respectively. Conclusions: Three possible conclusions can be drawn from these results: 1) the peaks identified are spurious findings, 2) additional genes physically close to LMNA, PPARG, or within 9q, are involved in FPLD etiology, or 3) alternative disease causing mechanisms not identified by standard exon sequencing approaches, such as promoter mutations, alternative splicing, or epigenetics, are also responsible for FPLD.


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