Progression and regression of kidney disease in type 1 diabetes

Diabetic kidney disease is distinguished by the presence of albuminuria, hypertension, declining kidney function, and a markedly elevated cardiovascular disease risk. This constellation of clinical features drives the premature mortality associated with type 1 diabetes. The first epidemiological investigations concerning type 1 diabetes-related albuminuria date back to the 1980s. The early studies found that proteinuria - largely equivalent to severe albuminuria - developed in 35 to 45% of individuals with type 1 diabetes, with the diabetes duration-specific incidence rate pattern portraying one or two peaks. Furthermore, moderate albuminuria, the first detectable sign of diabetic kidney disease, was found to nearly inexorably progress to overt kidney disease within a short span of time. Since the early reports, studies presenting more updated incidence rates have appeared, although significant limitations such as study populations that lack broad generalizability, study designs vulnerable to substantive selection bias, and constrained follow-up times have been encountered by many. Nevertheless, the most recent reports estimate that in modern times, moderate - instead of severe - albuminuria develops in one-third of individuals with type 1 diabetes; yet, a considerable part (up to 40% during the first ten years after the initial albuminuria diagnosis) progresses to more advanced stages of the disease over time. An alternative pathway to albuminuria progression is its regression, which affects up to 60% of the individuals, but notably, the relapse rate to a more advanced disease stage is high. Whether albuminuria regression translates into a decline in cardiovascular disease and premature mortality risk is an area of debate, warranting more detailed research in the future. Another unclear but alarming feature is that although the incidence of severe albuminuria has fallen since the 1930s, the decline seems to have reached a plateau after the 1980s. This stagnation may be due to the lack of kidney-protective medicines since the early 1980s, as the recent breakthroughs in type 2 diabetes have not been applicable to type 1 diabetes. Therefore, novel treatment strategies are at high priority within this patient population.

Clinical features and spectrum of NOTCH3 variants in Finnish patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL)

OBJECTIVES

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a cerebral small vessel disease caused by pathogenic variants in the NOTCH3 gene. In Finland, the majority of CADASIL patients carry the pathogenic founder variant c.397C>T, (p.Arg133Cys), but the spectrum of other NOTCH3 variants has not been investigated previously. The aim of the study was to investigate the spectrum and prevalence of NOTCH3 variants Finnish CADASIL patients and to examine the clinical features associated with them.

MATERIALS AND METHODS

The spectrum of NOTCH3 variants and the clinical features associated with them were retrospectively examined in 294 Finnish CADASIL patients tested during January 1996 to October 2021 in the Medical Genetics laboratory of Department of Genomics of Turku University Hospital, where practically all samples of patients with suspected CADASIL in Finland are investigated.

RESULTS

The most common NOTCH3 variants in the study cohort were c.397C>T, (p.Arg133Cys) (68%) and c.3206A>G p.(Tyr1069Cys) (18%), but other less common NOTCH3 variants were detected in as many as 14% of the patients. Eight of the detected NOTCH3 variants were novel: c.520T>A,p.(Cys174Ser), c.836A>G,p.(Gln279Arg), c.1369T>G,p.(Cys457Gly), c.1338C>G,p.(Cys446Trp), c.1564T>G,p.(Cys522Gly), c.2848T>G,p.(Cys950Gly), c.6102dup,p.(Gly2035Argfs*60), and c.2410+6C>G. Other NOTCH3 variants than p.Arg133Cys and p.Tyr1069Cys were more often associated with more severe clinical features.

CONCLUSION

This study revealed the genetic and clinical spectrum of CADASIL in the Finnish population. Sequencing of the whole NOTCH3 gene performing a gene-panel or exome sequencing is recommended when suspecting CADASIL.

Prognostic Role of Tumor Immune Microenvironment in Pleural Epithelioid Mesothelioma

Background

Pleural mesothelioma (MPM) is an aggressive malignancy with an average patient survival of only 10 months. Interestingly, about 5%–10% of the patients survive remarkably longer. Prior studies have suggested that the tumor immune microenvironment (TIME) has potential prognostic value in MPM. We hypothesized that high-resolution single-cell spatial profiling of the TIME would make it possible to identify subpopulations of patients with long survival and identify immunophenotypes for the development of novel treatment strategies.

Methods

We used multiplexed fluorescence immunohistochemistry (mfIHC) and cell-based image analysis to define spatial TIME immunophenotypes in 69 patients with epithelioid MPM (20 patients surviving ≥ 36 months). Five mfIHC panels (altogether 21 antibodies) were used to classify tumor-associated stromal cells and different immune cell populations. Prognostic associations were evaluated using univariate and multivariable Cox regression, as well as combination risk models with area under receiver operating characteristic curve (AUROC) analyses.

Results

We observed that type M2 pro-tumorigenic macrophages (CD163+pSTAT1−HLA-DRA1−) were independently associated with shorter survival, whereas granzyme B+ cells and CD11c+ cells were independently associated with longer survival. CD11c+ cells were the only immunophenotype increasing the AUROC (from 0.67 to 0.84) when added to clinical factors (age, gender, clinical stage, and grade).

Conclusion

High-resolution, deep profiling of TIME in MPM defined subgroups associated with both poor (M2 macrophages) and favorable (granzyme B/CD11c positivity) patient survival. CD11c positivity stood out as the most potential prognostic cell subtype adding prediction power to the clinical factors. These findings help to understand the critical determinants of TIME for risk and therapeutic stratification purposes in MPM.