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Displaying publications 21 - 26 of 26 in total

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Genetic and clinical landscape of childhood cerebellar hypoplasia and atrophy

Sakamoto M, Iwama K, Sasaki M, Ishiyama A, Komaki H, Saito T, et al.

Genet Med, 2022 Dec;24(12):2453-2463.
PMID: 36305856 DOI: 10.1016/j.gim.2022.08.007

PURPOSE: Cerebellar hypoplasia and atrophy (CBHA) in children is an extremely heterogeneous group of disorders, but few comprehensive genetic studies have been reported. Comprehensive genetic analysis of CBHA patients may help differentiating atrophy and hypoplasia and potentially improve their prognostic aspects.
METHODS: Patients with CBHA in 176 families were genetically examined using exome sequencing. Patients with disease-causing variants were clinically evaluated.
RESULTS: Disease-causing variants were identified in 96 of the 176 families (54.5%). After excluding 6 families, 48 patients from 42 families were categorized as having syndromic associations with CBHA, whereas the remaining 51 patients from 48 families had isolated CBHA. In 51 patients, 26 aberrant genes were identified, of which, 20 (76.9%) caused disease in 1 family each. The most prevalent genes were CACNA1A, ITPR1, and KIF1A. Of the 26 aberrant genes, 21 and 1 were functionally annotated to atrophy and hypoplasia, respectively. CBHA+S was more clinically severe than CBHA-S. Notably, ARG1 and FOLR1 variants were identified in 2 families, leading to medical treatments.
CONCLUSION: A wide genetic and clinical diversity of CBHA was revealed through exome sequencing in this cohort, which highlights the importance of comprehensive genetic analyses. Furthermore, molecular-based treatment was available for 2 families.
Fulltext Identifying the Common Genetic Basis of Antidepressant Response

Pain O, Hodgson K, Trubetskoy V, Ripke S, Marshe VS, Adams MJ, et al.

Biol Psychiatry Glob Open Sci, 2022 Apr;2(2):115-126.
PMID: 35712048 DOI: 10.1016/j.bpsgos.2021.07.008

BACKGROUND: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction.
METHODS: Genome-wide analysis of remission (n remit = 1852, n nonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism-based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA.
RESULTS: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission (h 2 = 0.132, SE = 0.056) but not for percentage improvement (h 2 = -0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response.
CONCLUSIONS: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.
Fulltext Clinical practice guidelines for esophagogastric junction cancer: Upper GI Oncology Summit 2023

Kitagawa Y, Matsuda S, Gotoda T, Kato K, Wijnhoven B, Lordick F, et al.

Gastric Cancer, 2024 May;27(3):401-425.
PMID: 38386238 DOI: 10.1007/s10120-023-01457-3
Fulltext Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction

den Hoed J, de Boer E, Voisin N, Dingemans AJM, Guex N, Wiel L, et al.

Am J Hum Genet, 2021 02 04;108(2):346-356.
PMID: 33513338 DOI: 10.1016/j.ajhg.2021.01.007

Whereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression, and a severe phenotype. In contrast, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability.
Phylogenomics and the rise of the angiosperms

Zuntini AR, Carruthers T, Maurin O, Bailey PC, Leempoel K, Brewer GE, et al.

Nature, 2024 Apr 24.
PMID: 38658746 DOI: 10.1038/s41586-024-07324-0

Angiosperms are the cornerstone of most terrestrial ecosystems and human livelihoods1,2. A robust understanding of angiosperm evolution is required to explain their rise to ecological dominance. So far, the angiosperm tree of life has been determined primarily by means of analyses of the plastid genome3,4. Many studies have drawn on this foundational work, such as classification and first insights into angiosperm diversification since their Mesozoic origins5-7. However, the limited and biased sampling of both taxa and genomes undermines confidence in the tree and its implications. Here, we build the tree of life for almost 8,000 (about 60%) angiosperm genera using a standardized set of 353 nuclear genes8. This 15-fold increase in genus-level sampling relative to comparable nuclear studies9 provides a critical test of earlier results and brings notable change to key groups, especially in rosids, while substantiating many previously predicted relationships. Scaling this tree to time using 200 fossils, we discovered that early angiosperm evolution was characterized by high gene tree conflict and explosive diversification, giving rise to more than 80% of extant angiosperm orders. Steady diversification ensued through the remaining Mesozoic Era until rates resurged in the Cenozoic Era, concurrent with decreasing global temperatures and tightly linked with gene tree conflict. Taken together, our extensive sampling combined with advanced phylogenomic methods shows the deep history and full complexity in the evolution of a megadiverse clade.
Fulltext Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1

Klionsky DJ, Abdel-Aziz AK, Abdelfatah S, Abdellatif M, Abdoli A, Abel S, et al.

Autophagy, 2021 Jan;17(1):1-382.
PMID: 33634751 DOI: 10.1080/15548627.2020.1797280

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.