A novel nonsense variant in TPM4 caused dominant macrothrombocytopenia, mild bleeding tendency and disrupted cytoskeleton remodeling

Sparse matrix factorization robust to sample sharing across GWAS reveals interpretable genetic components

Complex trait-associated genetic variation is highly pleiotropic. This extensive pleiotropy implies that multi-phenotype analyses are informative for characterizing genetic associations, as they facilitate the discovery of trait-shared and trait-specific variants and pathways ("genetic factors"). Previous efforts have estimated genetic factors using matrix factorization (MF) applied to numerous GWAS. However, existing methods are susceptible to spurious factors arising from residual confounding due to sample-sharing in biobank GWAS. Furthermore, MF approaches have historically estimated dense factors, loaded on most traits and variants, that are challenging to map onto interpretable biological pathways. To address these shortcomings, we introduce "GWAS latent embeddings accounting for noise and regularization" (GLEANR), a MF method for detection of sparse genetic factors from summary statistics. GLEANR accounts for sample sharing between studies and uses regularization to estimate a data-driven number of interpretable factors. GLEANR is robust to confounding induced by shared samples and improves the replication of genetic factors derived from distinct biobanks. We used GLEANR to evaluate 137 diverse GWAS from the UK Biobank, identifying 58 factors that decompose the genetic architecture of input traits and have distinct signatures of negative selection and degrees of polygenicity. These sparse factors can be interpreted with respect to disease, cell-type, and pathway enrichment. We highlight three such factors capturing platelet measure phenotypes and enriched for disease-relevant markers corresponding to distinct stages of platelet differentiation. Overall, GLEANR is a powerful tool for discovering both trait-specific and trait-shared pathways underlying complex traits from GWAS summary statistics.

Application of platelet transcriptomics for assessing treatment effectiveness and predicting long-term platelet counts recovery in aplastic anemia

BACKGROUND

Aplastic anemia (AA) is a bone marrow failure disease for which the means of assessing and predicting the therapeutic effectiveness are still relatively limited. Thrombocytopenia is often the earliest and most severe symptom in patients newly diagnosed with AA. While clinical consideration is usually given to the quantitative changes in platelets during treatment, there is little focus on the resolution of the molecular characteristics of platelets in AA.

OBJECTIVES

To investigate the changes in platelet molecular characteristics throughout the treatment process of AA, and to explore the use of transcriptomics for monitoring and predicting treatment outcomes.

METHODS

We comprehensively analyzed platelet transcriptomic changes in patients with AA at initial diagnosis and different stages of treatment effectiveness using bulk transcriptome sequencing.

RESULTS

Genes associated with cell proliferation, erythroid function, and amino acid transport were elevated in newly diagnosed AA. Conversely, genes linked to histones, thrombopoiesis, mitochondrial energy metabolism, and signaling pathways were significantly downregulated. Additionally, 60.6% of the differentially expressed genes were substantially restored following complete remission. Furthermore, through the examination of longitudinal samples, we identified recovery ascending genes that could serve as viable biomarkers for assessing treatment effectiveness in AA. Besides, we observed that higher expression levels of recovery ascending genes may predict superior long-term platelet counts recovery 6 months in advance in patients with partial response.

CONCLUSION

The platelet transcriptome undergoes profound changes and can serve as a potential indicator for assessing treatment effectiveness and predicting long-term platelet counts recovery in AA.

Ischemic Stroke Thrombus Perviousness Is Associated with Distinguishable Proteomic Features and Susceptibility to ADAMTS13-Augmented Thrombolysis

BACKGROUND AND PURPOSE

Perviousness is the differential attenuation on CT of an intracranial arterial occlusive thrombus before and after IV contrast administration. While perviousness/permeability has been shown to be related to various clinical outcomes and reflects histopathologic composition, it remains unclear whether perviousness is also associated with differences in proteomic composition.

MATERIALS AND METHODS

Retrieved clots from 59 patients were evaluated with quantitative mass spectrometry. Proteomic differences between high-perviousness (≥11 HU) and low-perviousness (<11 HU) clots were investigated. Perviousness as a continuous variable was also correlated with protein abundance. Last, an ex vivo lysis assay was performed to investigate the differential susceptibility to tPA, deoxyribonuclease, and ADAMTS13 thrombolysis as a function of perviousness.

RESULTS

In total, 2790 distinct proteins were identified. Thrombus perviousness was associated with distinct proteomic features, including depletion of the macrophage marker CD14 (P = .039, z = 1.176) and hemoglobin subunit ζ (P = .046, z = 1.68) in pervious clots. Additionally, proteins involved in platelet cytoskeleton remodeling (tropomyosin α-3-chain) and granule secretion/aggregation (synaptotagmin-like protein 4/FC region receptor II-a) were associated with increasing perviousness (P < .006), among numerous other proteins. Monocyte/macrophage-associated proteins (apoptosis-associated specklike protein containing a CARD/SAMHD1) were also depleted in pervious emboli (P < .002). Ex vivo lysis indicated that pervious clots were more susceptible to ADAMTS13-augmented tPA thrombolysis compared with impervious clots (P < .05), though without differences in deoxyribonuclease digestion.

CONCLUSIONS

Thrombus perviousness is associated with complex proteomic features, including differential abundance of platelet-related proteins in highly permeable clots with monocyte/macrophage depletion. This association may help to explain why highly pervious thrombi were also found more susceptible to ADAMTS13-augmented thrombolysis.

Novel variants in GALE cause syndromic macrothrombocytopenia by disrupting glycosylation and thrombopoiesis

Glycosylation is recognized as a key process for proper megakaryopoiesis and platelet formation. The enzyme uridine diphosphate (UDP)-galactose-4-epimerase, encoded by GALE, is involved in galactose metabolism and protein glycosylation. Here, we studied 3 patients from 2 unrelated families who showed lifelong severe thrombocytopenia, bleeding diathesis, mental retardation, mitral valve prolapse, and jaundice. Whole-exome sequencing revealed 4 variants that affect GALE, 3 of those previously unreported (Pedigree A, p.Lys78ValfsX32 and p.Thr150Met; Pedigree B, p.Val128Met; and p.Leu223Pro). Platelet phenotype analysis showed giant and/or grey platelets, impaired platelet aggregation, and severely reduced alpha and dense granule secretion. Enzymatic activity of the UDP-galactose-4-epimerase enzyme was severely decreased in all patients. Immunoblotting of platelet lysates revealed reduced GALE protein levels, a significant decrease in N-acetyl-lactosamine (LacNAc), showing a hypoglycosylation pattern, reduced surface expression of gylcoprotein Ibα-IX-V (GPIbα-IX-V) complex and mature β1 integrin, and increased apoptosis. In vitro studies performed with patients-derived megakaryocytes showed normal ploidy and maturation but decreased proplatelet formation because of the impaired glycosylation of the GPIbα and β1 integrin, and reduced externalization to megakaryocyte and platelet membranes. Altered distribution of filamin A and actin and delocalization of the von Willebrand factor were also shown. Overall, this study expands our knowledge of GALE-related thrombocytopenia and emphasizes the critical role of GALE in the physiological glycosylation of key proteins involved in platelet production and function.