Biology subjects

Malawsky, D. S.

Publications and source records attributed to Malawsky, D. S..

3 recordsLinked to original sources

bioRxiv2026

Phantom genetic nurture: assortative mating accounts for most of the apparent association between parental genotypes and childhood cognitive performance

Parental genotypes may influence offspring outcomes through the environments parents provide, a process known as genetic nurture, but estimating such effects from polygenic scores is complicated jointly by measurement error, unobserved genetic variation, and assortative mating. Here, we introduce RAVEL, a structural equation modeling framework that uses two independently constructed polygenic scores for the same trait to estimate latent genetic liability associations in parent-offspring trios and to distinguish direct and non-transmitted genetic associations. Through analytic derivations and simulations, we show that naive trio regressions can produce spurious non-zero parental coefficients, attenuate genuine genetic nurture effects, and obscure asymmetric parental effects, whereas RAVEL recovers unbiased estimates of the underlying coefficients when the assortative mating history and the extent of unobserved genetic variation are correctly specified. Applying RAVEL to national test scores in the Norwegian Mother, Father and Child Cohort Study using polygenic scores for educational attainment, we find that parental genetic liabilities explain less than 0.5% as much variance in childhood cognitive performance as the child's own genetic liability (substantially lower than the 10% observed with naive trio regressions) once assortative mating is modeled, with only a small paternal association significantly surviving the correction. In contrast, we find a maternal-specific non-transmitted association with offspring premature birth. RAVEL provides a general framework for interpreting trio polygenic score analyses of direct and non-transmitted genetic effects, clarifying the contribution of parental genetic liabilities to offspring traits.

genetics↗

bioRxiv2021

Chronic AMPK inactivation slows SHH medulloblastoma progression by inhibiting mTORC1 signaling and depleting tumor stem cell populations

We show that inactivating AMPK in vivo in a genetic model of medulloblastoma depletes tumor stem cell populations and slows tumor progression. Medulloblastoma, the most common malignant pediatric brain tumor, grows as heterogenous communities comprising diverse types of tumor and stromal cells. Previously, we showed that different populations in medulloblastomas show different sensitivities to specific targeted therapies. To determine if specific populations depend on AMPK, we analyzed mice with AMPK-inactivated medulloblastomas. We engineered mice with conditional deletion of the AMPK catalytic subunits Prkaa1 and Prkaa2 and conditional expression SmoM2, an oncogenic Smo allele that hyperactivates Sonic Hedgehog (SHH) signaling. We compared these medulloblastomas to SmoM2-driven medulloblastomas in AMPK-intact mice. AMPK-inactivation slowed tumor growth and progression, allowing longer event-free survival (EFS). scRNA-seq showed that AMPK inactivation altered cellular heterogeneity, increasing differentiation, decreasing tumor stem cell populations and reducing glio-neuronal multipotency. Surprisingly, AMPK-inactivated tumors showed decreased mTORC1 activation and Hk2 expression. Genetic Hk2 deletion in SmoM2-medulloblastomas similarly decreased stem cell populations, implicating reduced aerobic glycolysis in the tumor-suppressive effect of AMPK inactivation. Our results show that AMPK inactivation impairs tumor growth through mechanisms that disproportionately affect tumor stem cell populations that have proved refractory to conventional therapies.

cancer biology↗

bioRxiv2020

Neoplastic and Immune single cell transcriptomics define subgroup-specific intra-tumoral heterogeneity of childhood medulloblastoma.

Medulloblastoma (MB) is a heterogeneous disease in which neoplastic cells and associated immune cells contribute to disease progression. To better understand cellular heterogeneity in MB we use single-cell RNA sequencing, immunohistochemistry and deconvolution of transcriptomic data to profile neoplastic and immune populations in childhood MB samples. Neoplastic cells cluster primarily according to individual sample of origin which is in part due to the effect of chromosomal copy number gains and losses. Harmony alignment reveals novel MB subgroup/subtype-associated subpopulations that recapitulate neurodevelopmental processes and are associated with clinical outcomes, including discrete photoreceptor-like cells in MB subgroups GP3 and GP4 and nodule-associated neuronally-differentiated cells in subgroup SHH. We definitively chart the spectrum of MB immune cell infiltrates, which include subgroup/subtype-associated developmentally-related neuron-pruning and antigen presenting myeloid cells. MB cellular diversity is recapitulated in genetically engineered mouse subgroup-specific models of MB. These findings provide a clearer understanding of both the neoplastic and immune cell heterogeneity in MB.

cancer biology↗