Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes

Approaches to Measuring Beta Cell Reserve and Defining Partial Clinical Remission in Paediatric Type 1 Diabetes

CONTEXT

Type 1 diabetes (T1D) results from the autoimmune T-cell mediated destruction of pancreatic beta cells leading to insufficient insulin secretion. At the time of diagnosis of T1D, there is residual beta cell function that declines over the subsequent months to years. Recent interventions have been approved to preserve beta cell function in evolving T1D.

OBJECTIVE

The aim of this review is to summarise the approaches used to assess residual beta cell function in evolving T1D, and to highlight potential future directions.

METHODS

Studies including subjects aged 0 to 18 years were included in this review. The following search terms were used; "(type 1 diabetes) and (partial remission)" and "(type 1 diabetes) and (honeymoon)". References of included studies were reviewed to determine if additional relevant studies were eligible.

RESULTS

There are numerous approaches to quantifying beta cell reserve in evolving T1D. These include c-peptide measurement after a mixed meal or glucagon stimuli, fasting c-peptide, the urinary c-peptide/creatinine ratio, insulin dose-adjusted haemoglobin A1c, and other clinical models to estimate beta cell function. Other biomarkers may have a role, including the proinsulin/c-peptide ratio, cytokines, and microRNA. Studies using thresholds to determine if residual beta cell function is present often differ in values used to define remission.

CONCLUSIONS

As interventions are approved to preserve beta cell function, it will become increasingly necessary to quantify residual beta cell function in research and clinical contexts. In this report, we have highlighted the strengths and limitations of the current approaches.

HOMA-IR and the Matsuda Index as predictors of progression to type 1 diabetes in autoantibody-positive relatives

AIM/HYPOTHESIS

We assessed whether HOMA-IR and the Matsuda Index are associated with transitions through stages of type 1 diabetes.

METHODS

Autoantibody (AAb)-positive relatives of individuals with type 1 diabetes (n=6256) from the TrialNet Pathway to Prevention were studied. Associations of indicators of insulin resistance (HOMA-IR) and insulin sensitivity (Matsuda Index) with BMI percentile (BMIp) and age were assessed with adjustments for measures of insulin secretion, Index60 and insulinogenic index (IGI). Cox regression was used to determine if tertiles of HOMA-IR and Matsuda Index predicted transitions from Not Staged (<2 AAbs) to Stage 1 (≥2 AAbs and normoglycaemia), from Stage 1 to Stage 2 (≥2 AAbs with dysglycaemia), and progression to Stage 3 (diabetes as defined by WHO/ADA criteria).

RESULTS

There were strong associations of HOMA-IR (positive) and Matsuda Index (inverse) with baseline age and BMIp (p<0.0001). After adjustments for Index60, transitioning from Stage 1 to Stage 2 was associated with higher HOMA-IR and lower Matsuda Index (HOMA-IR: HR=1.71, p<0.0001; Matsuda Index, HR=0.40, p<0.0001), as with progressing from Stages 1 or 2 to Stage 3 (HOMA-IR: HR=1.98, p<0.0001; Matsuda Index: HR=0.46, p<0.0001). Without adjustments, associations of progression to Stage 3 were inverse for HOMA-IR and positive for Matsuda Index, opposite in directionality with adjustments. When IGI was used in place of Index60, the findings were similar.

CONCLUSIONS/INTERPRETATION

Progression to Stages 2 and 3 of type 1 diabetes increases with HOMA-IR and decreases with the Matsuda Index after adjustments for insulin secretion. Indicators of insulin secretion appear helpful for interpreting associations of progression to type 1 diabetes with HOMA-IR or the Matsuda Index in AAb-positive relatives.

Autoimmune polyglandular syndrome type 4: experience from a single reference center

Purpose

To characterize patients with APS type 4 among those affected by APS diagnosed and monitored at our local Reference Center for Autoimmune Polyglandular Syndromes.

Methods

Monocentric observational retrospective study enrolling patients affected by APS diagnosed and monitored in a Reference Center. Clinical records were retrieved and analyzed.

Results

111 subjects (51 males) were affected by APS type 4, mean age at the onset was 23.1 ± 15.1 years. In 15 patients the diagnosis of APS was performed during the first clinical evaluation, in the other 96 after a latency of 11 years (range 1-46). The most frequent diseases were type I diabetes mellitus and celiac disease, equally distributed among sexes.

Conclusions

The prevalence of APS type 4 is 9:100,000 people. Type I diabetes mellitus was the leading indicator of APS type 4 in 78% subjects and in 9% permitted the diagnosis occurring as second manifestation of the syndrome. Our data, showing that 50% of patients developed APS type 4 within the first ten years, don't suggest any particular follow-up time and, more importantly, don't specify any particular disease. It is important to emphasize that 5% of women developed premature ovarian failure.

Human immune phenotyping reveals accelerated aging in type 1 diabetes

The proportions and phenotypes of immune cell subsets in peripheral blood undergo continual and dramatic remodeling throughout the human life span, which complicates efforts to identify disease-associated immune signatures in type 1 diabetes (T1D). We conducted cross-sectional flow cytometric immune profiling on peripheral blood from 826 individuals (stage 3 T1D, their first-degree relatives, those with ≥2 islet autoantibodies, and autoantibody-negative unaffected controls). We constructed an immune age predictive model in unaffected participants and observed accelerated immune aging in T1D. We used generalized additive models for location, shape, and scale to obtain age-corrected data for flow cytometry and complete blood count readouts, which can be visualized in our interactive portal (ImmScape); 46 parameters were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with accelerated immunological aging in T1D included increased CXCR3+ and programmed cell death 1-positive (PD-1+) frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels on memory T cells. Phenotypes associated with T1D after age correction were predictive of T1D status. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.